Transmission apparatus and method, and reception apparatus and method

ABSTRACT

An encoding method changes an encoding rate of an erasure correcting code. One cycle is defined as 12k bits (wherein k represents a natural number) which is an encoding output using LDPC-CC with an encoding rate of 1/2, and includes information and parity. From the one cycle, only the information is arranged in the output order of the encoding output to obtain 6k bit information X6i, X6i+1, X6i+2, X6i+3, X6i+4, X6i+5, . . . , X6(i+k−1) X6(i+k−1)+1, X6(i+k−1)+2, X6(i+k−1)+3, X6(i+k−1)+4, and X6(i+k−1)+5. Known information is inserted in 3k pieces of information (Xj) among the 6k bit information, so that when 3k pieces of mutually different j is divided by 3, there is a remainder of 0 regarding k pieces, there is a remainder of 1 regarding k pieces, and there is a remainder of 2 regarding k pieces, to thereby obtain the parity from the information containing the known information.

CROSS REFERENCE TO RELATED APPLICATIONS

This is a continuation application of application Ser. No. 14/709,175filed May 11, 2015, which is a continuation application of applicationSer. No. 14/242,545 filed Apr. 1, 2014, which is a continuationapplication of application Ser. No. 13/142,212 filed Jun. 24, 2011,which is a 371 application of PCT/JP2009/007011 filed Dec. 18, 2009,which is based on Japanese Application No. 2008-334028 filed Dec. 26,2008, the entire contents of each of which are incorporated by referenceherein.

TECHNICAL FIELD

The present invention relates to an encoding method, an encoder and adecoder that perform erasure correction encoding using, for example, lowdensity parity check codes (LDPC Codes).

BACKGROUND ART

For application such as moving image streaming, when more than atolerable number of packets are lost at an application level, errorcorrection codes are used to secure quality. For example, PatentLiterature 1 discloses a method of creating redundant packets for aplurality of information packets using a Reed-Solomon code andtransmitting the information packets with the redundant packets attachedthereto. By so doing, even when packets are lost, the erased packets canbe decoded as long as the loss is within the range of error correctioncapability of the Reed-Solomon code.

However, when a number of packets beyond the correction capability ofthe Reed-Solomon code are lost, or packets are continuously lost due tofading or the like in a wireless communication channel over a relativelylong period of time and burst erasure occurs, erasure correction may notbe effectively performed. When the Reed-Solomon code is used, althoughthe correction capability can be improved by increasing the block lengthof the Reed-Solomon code, there is a problem that the amount ofcomputation of coding/decoding processing and the circuit scale willincrease.

To solve such a problem, low-density parity check (LDPC) codes arebecoming a focus of attention as an error correction code for packeterasure. LDPC codes are codes defined in a very sparse check matrix andcan perform coding/decoding processing with a practical time/operationcost even when the code length is on the order of several thousands toseveral tens of thousands.

FIG. 1 illustrates a conceptual diagram of a communication system usingerasure correction encoding by an LDPC code (see Non-Patent Literature1). In FIG. 1, a communication apparatus 1011 on an encoding sideperforms LDPC encoding on information packets 1001 (“1” to “4”) totransmit and generates parity packets 1002 (“a” and “b”). A processingsection of upper layer 1012 outputs an encoded packet with a paritypacket 1002 added to an information packet 1001 to a lower layer 1013(physical layer (PHY) in the example in FIG. 1) and a physical layerprocessing section in the lower layer 1013 converts the encoded packetinto a format in which the packet is transmittable through acommunication channel 1031 and outputs the packet to the communicationchannel 1031. FIG. 1 shows an example where the communication channel1031 is a wireless communication channel.

A communication apparatus 1021 on a decoding side performs receptionprocessing by a physical layer processing section of a lower layer 1023.At this time, suppose a bit error has occurred in the lower layer 1023.Due to this bit error, a packet 1003 including the corresponding bitcannot be correctly decoded in the upper layer 1022 and packet erasuremay result. The example in FIG. 1 shows a case where information packet1003 (“3”) is lost. The processing section of upper layer 1022 appliesLDPC decoding processing to a received packet sequence and therebydecodes lost information packet 1003 (“3”). For LDPC decoding,sum-product decoding that performs decoding using belief propagation(BP) or a Gaussian elimination method or the like is used.

FIG. 2 is an overall configuration diagram of the above-describedcommunication system. In FIG. 2, the communication system includescommunication apparatus 10 on the encoding side, communication channel20 and communication apparatus 30 on the decoding side. Communicationapparatus 10 on the encoding side includes packet generation section 11,erasure correction encoding-related processing section 12, errorcorrecting encoding section 13 and transmitting apparatus 14, andcommunication apparatus 30 on the decoding side includes receivingapparatus 31, error correcting decoding section 32, erasure correctiondecoding related processing section 33 and packet decoding section 34.Communication channel 20 represents a channel through which a signaltransmitted from transmitting apparatus 14 of communication apparatus 10on the encoding side passes until the signal is received by receivingapparatus 31 of communication apparatus 30 on the decoding side. Forcommunication channel 20, Ethernet (registered trademark), power line,metal cable, optical fiber, radio, light (visible light, infrared or thelike) or a combination thereof can be used. Furthermore, errorcorrecting encoding section 13 introduces error correction codes in thephysical layer besides erasure correction codes to correct errorsproduced in communication channel 20. Therefore, error correctingdecoding section 32 decodes error correction codes in the physicallayer.

The erasure correction encoding method in erasure correctionencoding-related processing section 12 will be described using FIG. 3.

Packet generation section 11 receives information 41 as input, generatesinformation packet 43 and output information packet 43 to rearrangingsection 15. Hereinafter, a case where information packet 43 is made upof information packets #1 to #n will be described as an example.

Rearranging section 15 receives information packet 43 (here, informationpackets #1 to #n) as input, reorders the information and outputsreordered information 45.

Erasure correction encoder (parity packet generation section) 16receives reordered information 45 as input, performs encoding of, forexample, an LDPC-BC (low-density parity-check block code, e.g., seeNon-Patent Literature 2) or LDPC-CC (low-density parity-checkconvolutional code, e.g., see Non-Patent Literature 3) on information 45and generates a parity part. Erasure correction encoder (parity packetgeneration section) 16 extracts only the parity part generated,generates parity packet 47 from the extracted parity part and outputsthe parity packet 47. In this case, when parity packets #1 to #m aregenerated for information packets #1 to #n, parity packet 47 becomesparity packets #1 to #m.

Error detection code adding section 17 receives information packet 43(information packets #1 to #n), and parity packet 47 (parity packets #1to #m) as input, adds an error detection code, for example, a CRC(Cyclic Redundancy Check) check part to information packet 43(information packets #1 to #n) and parity packet 47 (parity packets #1to #m) and outputs information packet and parity packet 49 with a CRCcheck part. Therefore, information packet and parity packet 49 with aCRC check part are made up of information packets #1 to #n and paritypackets #1 to #m with a CRC check part.

The erasure correction decoding method by erasure correction decodingrelated processing section 33 will be described using FIG. 4.

Error detection section 35 receives packet 51 after decoding the errorcorrection code in the physical layer as input and performs errordetection using, for example, CRC check. In this case, packet 51 afterthe error correction code decoding in the physical layer is made up ofdecoded information packets #1 to #n and decoded parity packets #1 to#m. When erased packets are detected in the decoded information packetsand decoded parity packets as a result of the error detection as shown,for example, in FIG. 4, error detection section 35 assigns packetnumbers to the information packets and parity packets in which packeterasure has not occurred and outputs those packets as packet 53.

Erasure correction decoder 36 receives packet 53 (information packets(with packet number) and parity packets (with packet number)) in whichpacket erasure has not occurred) as input, performs erasure correctioncode decoding and decodes information packet 55 (information packets #1to #n).

CITATION LIST Patent Literature

PTL 1

-   Japanese Patent Application Laid-Open No. 8-186570

Non-Patent Literature

NPL 1:

-   Changyan Di, David Proietti, I. Emre Telatar, Thomas J. Richardson,    and Rudiger L. Urbanke, “Finite-Length Analysis of Low-Density    Parity-Check Codes on the Binary Erasure Channel,” IEEE Transactions    on Information Theory, vol. 48, No. 6, June 2002.    NPL 2:-   D. J. C. Mackay, “Good error-correcting codes based on very sparse    matrices,” IEEE Trans. Inform. Theory, vol. 45, no. 2, pp. 399-431,    March 1999.    NPL 3:-   A. J. Felstrom, and K. Sh. Zigangirov, “Time-Varying Periodic    Convolutional Codes With Low-Density Parity-Check Matrix,” IEEE    Transactions on Information Theory, Vol. 45, No. 6, pp 2181-2191,    September 1999.    NPL 4:-   R. G. Gallager, “Low-density parity check codes,” IRE Trans. Inform.    Theory, IT-8, pp-21-28, January 1962.    NPL 5:-   R. G. Gallager, “Low-Density Parity-Check Codes,” Cambridge, Mass.:    MIT Press, pp. 1-90, 1963.    NPL 6:-   M. P. C. Fossorier, M. Mihaljevic, and H. Imai, “Reduced complexity    iterative decoding of low density parity check codes based on belief    propagation,” IEEE Trans. Commun., vol. 47., no. 5, pp. 673-680, May    1999.    NPL 7:-   J. Chen, A. Dholakia, E. Eleftheriou, M. P. C. Fossorier, and X.-Yu    Hu, “Reduced-complexity decoding of LDPC codes,” IEEE Trans.    Commun., vol. 53, no. 8, pp. 1288-1299, August 2005.    NPL 8:-   J. Zhang, and M. P. C. Fossorier, “Shuffled iterative decoding,”    IEEE Trans. Commun., vol. 53, no. 2, pp. 209-213, February 2005.    NPL 9:-   J. M. Wozencraft, and B. Reiffen, “Sequential decoding,” MIT Press,    pp. 24-57, Cambridge, 1961.    NPL 10:-   A. J. Viterbi, “Error bounds for convolutional codes and an    asymptotically optimum decoding algorithm,” IEEE Trans. Inform.    Theory, Vol. IT-13, No. 2, pp. 260-269, April 1967.    NPL 11:-   K. J. Larsen, “Short convolutional codes with maximal free distance    for rates 1/2, 1/3, and 1/4,” IEEE Trans. Inform. Theory, IT-19, no.    3, pp. 371-372, May 1973.    NPL 12:-   D. G. Daut, J. W. Modestino, and L. D. Wismer, “New short constraint    length convolutional code construction for selected rational rates,”    IEEE Trans. Inform. Theory, Vol. IT-28, no. 5, pp. 794-800,    September 1982.    NPL 13:-   D. J. Costello Jr., “Free distance bounds for convolutional codes,”    IEEE Trans. Inform. Theory, vol. IT-20, no. 3, pp. 356-365, May    1974.    NPL 14:-   P. J. Lee, “There are many good periodically time-varying    convolutional codes,” IEEE Trans. Inform. Theory, vol. 35, no. 2,    pp. 460-463, March 1989.    NPL 15:-   F. R. Kschischang, B. J. Frey, and H. Loeliger, “Factor graphs and    the sum-product algorithm,” IEEE Trans. Inform. Theory, vol. 47, no.    2, pp. 498-519, February 2001.    NPL 16:-   R. J. McElicce, D. J. C. MacKay, and J.-F. Cheng, “Turbo decoding as    an instance of Perl's “belief propagation” algorithm,” IEEE J.    Select. Areas Commun., vol. 16, no. 2, pp. 140-152, February 1998.    NPL 17:-   J. L. Fan, “Array codes as low-density parity-check codes,” Proc. of    2nd Int. Symp. on Turbo Codes & Related Topics, pp. 543-546,    September 2000.    NPL 18:-   Y. Kou, S. Lin, and M. P. C. Fossorier, “Low-density parity-check    codes based on finite geometries: A rediscovery and new results,”    IEEE Trans. Inform. Theory, vol. 47, no. 7, pp. 2711-2736. November    2001.    NPL 19:-   M. P. C. Fossorier, “Quasi-cyclic low-density parity-check codes    from circulant permutation matrices,” IEEE Trans. Inform. Theory,    vol. 50, no. 8, pp. 1788-1793, August 2004.    NPL 20:-   L. Chen, J. Xu, 1. Djurdjevic, and S. Lin, “Near-Shannon-limit    quasi-cyclic low-density parity-check codes,” IEEE Trans. Commun.,    vol. 52, no. 7, pp. 1038-1042, July 2004.    NPL 21:-   R. M. Tanner, D. Sridhara, A. Sridharan, T. E. Fuja, and D. J.    Costello Jr., “LDPC block and convolutional codes based on circulant    matrices,” IEEE Trans. Inform. Theory, vol. 50, no. 12, pp.    2966-2984, December 2004.    NPL 22:-   A. Pusane, R. Smarandache, P. Vontobel, and D. J. Costello Jr., “On    deriving good LDPC convolutional codes from QC LDPC block codes,”    Proc. of IEEE ISIT 2007, pp. 1221-1225, June 2007.    NPL 23:-   J. Rosenthal, and E. V. York, “BCH convolutional codes,” IEEE Trans.    Inform. Theory, vol. 45, no. 6, pp. 1833-1844, September 1999.    NPL 24:-   N. Ogasahara, M. Kobayashi, and S. Hirasawa, “The construction of    periodically time-variant convolutional codes using binary linear    block codes,” IEICE Trans. Fundamentals, vol. J89-A, no. 2, pp.    144-153, February 2006 (in Japanese).    NPL 25:-   Y. Murakami, S. Okasaka, S. Okamura, T. Kishigami, and M. Orihashi,    “LDPC convolutional codes based on parity check polynomial,” Proc.    of WPMC2008, IEICE Technical Report, RCS2008-13, Vol. 108, No. 61,    pp. 75-79, May 29, 2008.    NPL 26:-   Y. Murakami, S. Okamura, S. Okasaka, T. Kishigami, and M. Orihashi,    “LDPC convolutional codes based on parity check polynomials with a    time period of 3,” IEICE Trans. Fundamentals, vol. E92-A, no. 10,    pp. 2479-2483, October 2009.

SUMMARY OF INVENTION Technical Problem

When thinking of improvement of transmission efficiency and improvementof erasure correction capability, it is desirable to enable a codingrate in an erasure correction code to be changed by means ofcommunication quality such as a transmission path situation. FIG. 5shows a configuration example of an erasure correction encoder capableof changing a coding rate of an erasure correction code according tocommunication quality such as a transmission path situation.

First erasure correction encoder 61 is an encoder of an erasurecorrection code of a coding rate of 1/2, second erasure correctionencoder 62 is an encoder of an erasure correction code of a coding rateof 2/3 and third erasure correction encoder 63 is an encoder of anerasure correction code of a coding rate of 3/4.

First erasure correction encoder 61 receives information 71 and controlsignal 72 as input, performs encoding when control signal 72 specifies acoding rate of 1/2 and outputs data 73 after erasure correction encodingto selection section 64. Similarly, second erasure correction encoder 62receives information 71 and control signal 72 as input, performsencoding when control signal 72 specifies a coding rate of 2/3 andoutputs data 74 after erasure correction encoding to selection section64. Similarly, third erasure correction encoder 63 receives information71 and control signal 72 as input, performs encoding when control signal72 specifies a coding rate of 3/4 and outputs data 75 after erasurecorrection encoding to selection section 64.

Selection section 64 receives data 73, 74 and 75 after erasurecorrection encoding and control signal 72 as input, and outputs data 76after erasure correction encoding corresponding to the coding ratespecified by control signal 72.

In this case, the erasure correction encoders in FIG. 5 need to preparean erasure correction encoder which differs from one coding rate toanother to change the coding rate of an erasure correction code and havea problem that the circuit scales of the erasure correction encoders anderasure correction decoders increase. However, there are not sufficientstudies on erasure correction encoding and erasure decoding methodscapable of reducing the circuit scales of erasure correction encodersand erasure correction decoders.

It is therefore an object of the present invention to provide anencoding method, an encoder and a decoder capable of changing a codingrate of an erasure correction code while reducing the circuit scales ofthe encoder and decoder.

Solution to Problem

The encoding method of the present invention is an encoding method ofgenerating a low-density parity check convolutional code (LDPC-CC) of acoding rate of 1/3 and a time varying period of 3 from a low-densityparity check convolutional code of a coding rate of 1/2 and a timevarying period of 3, where this low-density parity check convolutionalcode of a coding rate of 1/2 and a time varying period of 3 is definedbased on:

a first parity check polynomial in which (a1%3, a2%3, a3%3) and (b1%3,b2%3, b3%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2,0, 1) and (2, 1, 0) of a parity check polynomial represented by equation3-1,

a second parity check polynomial in which (A1%3, A2%3, A3%3) and (B1%3,B2%3, B3%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0) and(2, 0, 1), (2, 1, 0) of a parity check polynomial represented byequation 3-2, and

a third parity check polynomial in which (a1%3, ca2%3, a3%3) and (01%3,P2%3, P3%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2,0, 1) and (2, 1, 0) of a parity check polynomial represented by equation3-3, the method including the steps of:

inserting, when inserting known information into information Xj of 3kbits (where j takes a value of any of 6i to 6 (i+k−1)+5, and there are3k different values) of 6 k bits of information X_(6i), X_(6i+1),X_(6i+2), X_(6i+3), X_(6i+4), X_(6i+5), . . . , X_(6(i+k−1)),X_(6(i+k−1)+1), X_(6(i+k−1)+2), X_(6(i+k−1)+3), X_(6(i+k−1)+4),X_(6(i+k−1)+5) which is only information arranged in output order ofencoded outputs from one period of 12k (k is a natural number) bitscomposed of information and parity part which are the encoded outputsusing the low-density parity check convolutional code of a coding rateof 1/2, the known information into the information Xj such that, ofremainders after dividing 3k different j's by 3, the number ofremainders which become 0 is k, the number of remainders which become 1is k and the number of remainders which become 2 is k; and

obtaining the parity part from the information including the knowninformation.

Advantageous Effects of Invention

According to the present invention, it is possible to change a codingrate of an erasure correction code while reducing the circuit scales ofan encoder and decoder, and thereby realize both improvement oftransmission efficiency and improvement of erasure correctioncapability.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram illustrating a conceptual diagram of a communicationsystem using erasure correction encoding;

FIG. 2 is a diagram illustrating an overall configuration of acommunication system that performs erasure correction;

FIG. 3 is a diagram illustrating an erasure correction encoding method;

FIG. 4 is a diagram illustrating an erasure correction decoding method;

FIG. 5 is a block diagram illustrating a configuration example of anerasure correction encoder capable of changing a coding rate of anerasure correction code;

FIG. 6 is a diagram illustrating an overall configuration of acommunication system according to Embodiment 1 of the present invention;

FIG. 7 is a block diagram illustrating a detailed configuration of aportion associated with a change of the coding rate of the erasurecorrection code in the communication apparatus in FIG. 6;

FIG. 8 is a block diagram illustrating another detailed configuration ofthe portion associated with a change of the coding rate of the erasurecorrection code in the communication apparatus in FIG. 6;

FIGS. 9A to 9D are packet configuration diagrams illustrating operationsof a portion associated with a change of the coding rate of the erasurecorrection code;

FIGS. 10A to 10D are packet configuration diagrams illustratingoperations of a portion associated with a change of the coding rate ofthe erasure correction code;

FIG. 11 is a block diagram illustrating a configuration of atransmitting apparatus for transmitting information of the coding rateof the erasure correction code to a communicating party;

FIG. 12 is a diagram illustrating a frame configuration example on thetime axis outputted from the transmitting apparatus;

FIG. 13 is a block diagram illustrating an example of a detailedconfiguration of the erasure correction decoding related processingsection;

FIG. 14 is a diagram illustrating parity check matrix H^(T)[0,n] of anLDPC-CC of a coding rate of R=1/2;

FIG. 15 is a diagram illustrating a configuration example of an encoderof an LDPC-CC defined by parity check matrix H^(T)[0, n];

FIG. 16 is a diagram illustrating an example of a configuration of aparity check matrix of an LDPC-CC of a time varying period of 4;

FIG. 17A shows parity check polynomials of an LDPC-CC of a time varyingperiod of 3 and the configuration of parity check matrix H;

FIG. 17B shows the belief propagation relationship of terms relating toX(D) of “check equation #1” to “check equation #3” in FIG. 17A;

FIG. 17C shows the belief propagation relationship of terms relating toX(D) of “check equation #1” to “check equation #6”;

FIG. 18 is a diagram illustrating a parity check matrix of a (7, 5)convolutional code;

FIG. 19 is a diagram illustrating an example of the configuration ofparity check matrix H of an LDPC-CC of a coding rate of 2/3 and a timevarying period of 2;

FIG. 20 is a diagram illustrating an example of the configuration of aparity check matrix of an LDPC-CC of a coding rate of 2/3 and a timevarying period of m;

FIG. 21 is a diagram illustrating an example of the configuration of aparity check matrix of an LDPC-CC of a coding rate of (n−1)/n and a timevarying period of m;

FIG. 22 is a diagram illustrating an example of the configuration of anLDPC-CC encoding section;

FIG. 23 is a diagram illustrating an example of check equations of anLDPC-CC of a coding rate of 1/2 and parity check matrix H;

FIG. 24 is a diagram illustrating a shortening method [method #1-2];

FIG. 25 is a diagram illustrating an insertion rule in shortening method[method #1-2];

FIG. 26A is a diagram illustrating a relationship between a position atwhich known information is inserted and error correction capability;

FIG. 26B is a diagram illustrating the correspondence between a paritycheck polynomial 27-1 and points in time;

FIG. 27 is a diagram illustrating shortening method [method #2-2];

FIG. 28 is a diagram illustrating shortening method [method #2-4];

FIG. 29A is a block diagram illustrating an example of the configurationof a coding-related portion when the coding rate in a physical layer ismade variable;

FIG. 29B is a block diagram illustrating another example of theconfiguration of the coding-related portion in a physical layer when thecoding rate is made variable;

FIG. 30 is a block diagram illustrating an example of the configurationof an error correcting decoding section in the physical layer;

FIG. 31 is a diagram illustrating erasure correction method [method#3-1];

FIG. 32 is a diagram illustrating erasure correction method [method#3-3];

FIG. 33 is a diagram illustrating an example of a relationship betweenan information size and the number of terminations;

FIG. 34 is a diagram illustrating a Tanner graph;

FIG. 35 is a diagram illustrating a sub-matrix generated by extractingonly an X₁(D)-related portion from parity check matrix H; and

FIG. 36 is a diagram illustrating a vector generated by extracting onlyan X₁(D)-related portion from parity check matrix H.

DESCRIPTION OF EMBODIMENTS

Now, embodiments of the present invention will be described in detailwith reference to the accompanying drawings.

Embodiment 1

FIG. 6 is an overall configuration diagram of a communication systemaccording to Embodiment 1 of the present invention. In FIG. 6, thecommunication system includes communication apparatus 100 on an encodingside communication channel 20, and communication apparatus 200 on adecoding side. Communication channel 20 represents a path through whicha signal transmitted from transmitting apparatus 140 of communicationapparatus 100 on the encoding side passes until it is received byreceiving apparatus 210 of communication apparatus 200 on the decodingside. The communication system in FIG. 6 differs from the communicationsystem in FIG. 2 in that the communication system in FIG. 6 can changethe coding rate of an erasure correction code.

Receiving apparatus 210 of communication apparatus 200 receives a signaltransmitted from communication apparatus 100 and estimates acommunication state from control information signals such as pilotsignals and preambles of the received signal. Receiving apparatus 210then generates feedback information (e.g. Channel State Information) inaccordance with the communication state and outputs the feedbackinformation generated to transmitting apparatus 250. The feedbackinformation is transmitted from transmitting apparatus 250 tocommunication apparatus 100 through an antenna.

Receiving apparatus 150 of communication apparatus 100 sets a codingrate of the erasure correction code from the feedback informationtransmitted from communication apparatus 200 and outputs control signal404 including information of the set coding rate of the erasurecorrection code to packet generation and known packet insertion section110, erasure correction encoding-related processing section 120 anderror correcting encoding section 130.

Packet generation and known packet insertion section 110 receivesinformation 101, control signal 404 including information on the codingrate of the erasure correction code and setting signal 401 as input, andgenerates an information packet based on control signal 404 and settingsignal 401. To be more specific, packet generation and known packetinsertion section 110 generates an information packet from information101 and further inserts a known information packet into the informationpacket in accordance with the coding rate of the erasure correction codeincluded in control signal 404. Setting signal 401 includes informationset by communication apparatus 100 such as a packet size, modulationscheme. Details of operations of packet generation and known packetinsertion section 110 will be described later.

Erasure correction encoding-related processing section 120 receivescontrol signal 404 and setting signal 401 as input and performs erasurecorrection encoding on the information packet inputted from packetgeneration and known packet insertion section 110 based on controlsignal 404 and setting signal 401. An internal configuration andoperations of erasure correction encoding-related processing section 120will be described later.

To correct an error produced in communication channel 20, errorcorrecting encoding section 130 introduces an error correction code in aphysical layer in addition to the erasure correction code in erasurecorrection encoding-related processing section 120, performs errorcorrecting encoding on an input sequence inputted from erasurecorrection encoding-related processing section 120 and generates anencoded sequence.

Transmitting apparatus 140 performs predetermined processing (processingsuch as modulation, band limitation, frequency conversion,amplification) on the encoded sequence generated through errorcorrecting encoding in the physical layer by error correcting encodingsection 130.

Receiving apparatus 150 receives received signal 411 received throughthe antenna as input, performs predetermined processing (processing suchas band limitation, frequency conversion, amplification, demodulation)on received signal 411 and generates data 413.

Receiving apparatus 210 of communication apparatus 200 outputs signalsother than a control information signal of a received signal to errorcorrecting decoding section 220.

Error correcting decoding section 220 performs error correcting decodingin the physical layer on the signal inputted from receiving apparatus210 and generates a decoded packet.

Erasure correction decoding related processing section 230 performserasure correction decoding on the decoded packet. The internalconfiguration and operations of erasure correction decoding relatedprocessing section 230 will be described later.

Packet decoding section 240 converts the packet after the erasurecorrection into a format analyzable by an information processing section(not shown).

Transmitting apparatus 250 receives feedback information andtransmission information as input, performs predetermined processing(processing such as modulation, band limitation, frequency conversion,amplification) on the feedback information and transmission information,generates transmission signal 415 and transmits transmission signal 415to communication apparatus 100 from, for example, an antenna.

FIG. 7 is a block diagram illustrating a detailed configuration of theportion associated with a change of the coding rate of the erasurecorrection code in communication apparatus 100 in FIG. 6. Components inFIG. 7 that operate in the same way as those in FIG. 6 are assigned thesame reference numerals.

Erasure correction encoding-related processing section 120 includeserasure correction encoding section 121, known information packetdeleting section 122 and error detection code adding section 123.

Rearranging section 1211 of erasure correction encoding section 121receives setting signal 401, control signal 404 and information packet103 (here, information packets #1 to #n) as input, rearranges theinformation in information packet 103 and outputs reordered information105.

Encoding section (parity packet generation section) 1212 of erasurecorrection encoding section 121 receives setting signal 401, controlsignal 404 and reordered information 105 as input, performs, forexample, an LDPC-BC or LDPC-CC encoding and generates a parity part.Encoding section (parity packet generation section) 1212 extracts onlythe parity part generated, generates parity packet 107 from theextracted parity part and outputs parity packet 107. In this case, whenparity packets #1 to #m are generated in correspondence with informationpackets #1 to #n, parity packet 107 becomes parity packets #1 to #m.

Known information packet deleting section 122 receives informationpacket 103, setting signal 401 and control signal 404 as input andreduces part of information packet 103 based on the coding rate of theerasure correction code included in setting signal 401 and controlsignal 404. To be more specific, when packet generation and known packetinsertion section 110 inserts a known information packet intoinformation packet 103, known information packet deleting section 122deletes the known information packet from information packet 103 andoutputs information packet 104 after the deletion. Therefore, dependingon the coding rate, packet generation and known packet insertion section110 may not insert any known information packet into information packet103, and in such a case, known information packet deleting section 122does not delete the known information packet, but outputs informationpacket 103 as information packet 104 as is. Details of operations ofknown information packet deleting section 122 will be described later.

Error detection code adding section 123 receives parity packet 107,information packet 104 after the deletion, setting signal 401 andcontrol signal 404 as input, adds an error detection code, for example,a CRC check part to each packet and outputs each packet 109 with a CRCcheck part. Details of operations of error detection code adding section123 will be described later.

FIG. 8 is a block diagram illustrating another detailed configuration ofthe portion associated with a change of the coding rate of the erasurecorrection code in communication apparatus 100 in FIG. 6. As shown inFIG. 8, adopting a configuration in which information 101 inputted topacket generation and known packet insertion section 110 is inputted toerror detection code adding section 123 allows the communicationapparatus to operate in the same as in FIG. 7 even when knowninformation packet deleting section 122 in FIG. 7 is omitted.

The method of changing the coding rate of the erasure correction codeaccording to the present embodiment will be described using FIGS. 9A to9D and FIGS. 10A to 10D. FIGS. 9A to 9D (hereinafter collectively “FIG.9”) and FIGS. 10A to 10D (hereinafter collectively “FIG. 10”) show apacket configuration diagram illustrating operations of a portionassociated with a change of the coding rate of the erasure correctioncode in FIG. 7 and FIG. 8. A case will be described below where encodingsection (parity packet generation section) 1212 is made up of an encoderfor an erasure correction code of a coding rate of 2/3 and performserasure correction encoding of a coding rate of 2/3 as an example.

[Coding Rate 3/5]

A case will be described where the coding rate in erasure correctionencoding-related processing section 120 is set to 3/5 using an erasurecorrection code of a coding rate of 2/3.

To set the coding rate in erasure correction encoding-related processingsection 120 to 3/5, packet generation and known packet insertion section110 inserts a known information packet. To be more specific, as shown inFIG. 9, information packets #1 to #3 of information packets #1 to #4 aregenerated from information 101, while information packet #4 is generatedfrom known information predetermined with the communicating party, forexample, information all bits of which are “0.” With the knowninformation packet inserted in this way, information packet 103 is madeup of information packets #1 to #3 and known information packet #4.

Rearranging section 1211 receives information packet 103 as input,performs reordering and outputs reordered information packet 105.

Encoding section (parity packet generation section) 1212 receivesreordered information packet 105 as input and encodes the erasurecorrection code. Since encoding section (parity packet generationsection) 1212 is an encoder of a coding rate of 2/3, encoding section1212 generates two parity packets (parity packets #1 and #2) withrespect to information packet 103 made up of information packets #1 to#4 (see FIG. 9). Encoding section (parity packet generation section)1212 outputs parity packets #1 and #2 generated as parity packet 107.

Known information packet deleting section 122 deletes the knowninformation packet from information packet 103. In the example shown inFIG. 9, known information packet deleting section 122 receivesinformation packet 103 (information packets #1 to #3 and knowninformation packet #4) as input, deletes known information packet #4 asshown in FIG. 9 and outputs information packet 104 after deleting theknown information packet (that is, information packets #1 to #3).

Error detection code adding section 123 receives parity packet 107 andinformation packet 104 after deleting the known information packet asinput and outputs information packets #1 to #3 with a CRC check part andparity packets #1 and #2 with a CRC check part as shown in FIG. 9.

Thus, since erasure correction encoding-related processing section 120outputs information packets #1 to #3 with a CRC check part and paritypackets #1 and #2 with a CRC check part, the coding rate in erasurecorrection encoding-related processing section 120 can be set to 3/5.

As described above, when encoding section (parity packet generationsection) 1212 is an encoder of a coding rate of 2/3, by performingerasure correction encoding of a coding rate of 2/3 on three informationpackets #1 to #3 and one known information packet #4 and deletingencoded known information packet #4, encoding section (parity packetgeneration section) 1212 can set the coding rate to 3/5 as erasurecorrection encoding-related processing section 120 while performingencoding of a coding rate of 2/3.

Thus, even when encoding section (parity packet generation section) 1212does not provide any erasure correction code of a coding rate of 3/5,the coding rate in erasure correction encoding-related processingsection 120 can be set to 3/5, and therefore there is an advantage ofbeing able to reduce the circuit scale of the configurations shown inFIG. 7 and FIG. 8.

[Coding Rate of 1/2]

A case will be described using FIGS. 10A to 10D (hereinaftercollectively “FIG. 10”) where the coding rate in erasure correctionencoding-related processing section 120 is set to 1/2 using an erasurecorrection code of a coding rate of 2/3.

To set the coding rate in erasure correction encoding-related processingsection 120 to 1/2, packet generation and known packet insertion section110 inserts a known information packet. To be more specific, as shown inFIG. 10, information packets #1 and #2 of information packets #1 to #4are generated from information 101 and information packets #3 and #4 aregenerated from known information predetermined with the communicatingparty, for example, information all bits of which are “0.” With theknown information packets inserted in this way, information packet 103is made up of information packets #1 and #2 and known informationpackets #3 and #4.

Rearranging section 1211 receives information packet 103 as input,performs reordering and outputs reordered information packet 105.

Encoding section (parity packet generation section) 1212 receivesreordered information packet 105 as input and encodes the erasurecorrection code. Since encoding section (parity packet generationsection) 1212 is an encoder of a coding rate of 2/3, encoding section1212 generates two parity packets (parity packets #1 and #2) withrespect to information packet 103 made up of information packets #1 to#4 (see FIG. 10). Encoding section (parity packet generation section)1212 outputs parity packets #1 and #2 generated as parity packet 107.

Known information packet deleting section 122 deletes the knowninformation packet from information packet 103. In the example shown inFIG. 10, known information packet deleting section 122 receivesinformation packet 103 (information packets #1 and #2 and knowninformation packets #3 and #4) as input, deletes known informationpackets #3 and #4 as shown in FIG. 10 and outputs information packet 104after the deletion of the known information packets (that is,information packets #1 and #2).

Error detection code adding section 123 receives parity packet 107 andinformation packet 104 after the deletion of the known informationpackets as input and outputs information packets #1 and #2 with a CRCcheck part and parity packets #1 and #2 with a CRC check part as shownin FIG. 10.

Thus, information packets #1 and #2 with a CRC check part and paritypackets #1 and #2 with a CRC check part are outputted from erasurecorrection encoding-related processing section 120, and therefore thecoding rate in erasure correction encoding-related processing section120 can be set to 1/2.

As described above, when coding section (parity packet generationsection) 1212 is an encoder of a coding rate of 2/3, by performingerasure correction encoding of a coding rate of 2/3 on two informationpackets #1 and #2 and two known information packets #3 and #4 anddeleting encoded known information packets #3 and #4, coding section(parity packet generation section) 1212 can set the coding rate to 1/2as erasure correction encoding-related processing section 120 whileperforming encoding of a coding rate of 2/3.

In the case of a coding rate of 2/3, known information packets are notused and a coding rate of 2/3 can be realized by generating paritypackets #1 and #2 from information packets #1 to #4 not including knowninformation packets.

When communication apparatus 100 sets the coding rate of the erasurecorrection code (coding rate in erasure correction encoding-relatedprocessing section 120) from the feedback information transmitted fromcommunication apparatus 200, communication apparatus 100 needs to reportinformation of the set coding rate of the erasure correction code(coding rate in erasure correction encoding-related processing section120) to the communicating party. FIG. 1I is a block diagram illustratingthe configuration of transmitting apparatus 140 of communicationapparatus 100 for communication apparatus 100 to transmit information ofthe coding rate of the erasure correction code to communicationapparatus 200 which is the communicating party.

Control information generation section 142 receives setting signal 401relating to the erasure correction code, control signal 404 and othercontrol signal 403 as input, and generates and outputs controlinformation 405 to be transmitted to the communicating party. In thiscase, suppose control information 405 to be transmitted to thecommunicating party includes information on the coding rate set as thecoding rate in erasure correction encoding-related processing section120.

Modulation section 141 receives each packet 109 with a CRC check part,control Information 405 to be transmitted to the communicating party andframe configuration signal 406 as input, and generates and outputsmodulated signal 407 according to frame configuration signal 406.

Transmitting section 143 receives modulated signal 407 as input,performs predetermined processing (processing such as band limitation,frequency conversion, amplification) and outputs transmission signal408.

FIG. 12 is a diagram illustrating a frame configuration example oftransmission signal 408 outputted from transmitting apparatus 140 on thetime axis. In the example shown in FIG. 12, a frame is made up of acontrol information symbol 1101 and a data symbol 1102. In this case,suppose the data symbol 1102 is made up of a plurality of erasurecorrection blocks 1103. However, when the size of the data symbol 1102is small, the data symbol 1102 may be made up of one erasure correctionblock 1103.

Erasure correction encoding is by bundling a plurality of packets. Forexample, in the example of FIG. 9, four packets of information packets#1 to #4 are bundled and erasure correction encoding is performed basedon the unit of four packets. At this time, in the example of FIG. 9, theerasure correction block is made up of five packets with a CRC checkpart; information packets #1 to #3 excluding information packet #4 towhich known information is assigned and parity packets #1 and #2 with aCRC check part. Thus, the erasure correction block is made up of packetsexcept known information packets, generated based on the unit in whicherasure correction encoding is performed. Therefore, the coding rate inthe erasure correction block becomes the set coding rate. For example,in the example of FIG. 9, the erasure correction block is made up offive packets and since the number of information packets is three, thecoding rate in the erasure correction block is 3/5.

However, when the information to be transmitted is small, the codingrate in the erasure correction block does not always match the setcoding rate. When, for example, the information to be transmitted isequal to or less than information packet #1, known information isassigned to information packets #2 to #4, and the erasure correctionblock is made up of information packet #1 with a CRC check part andparity packets #1 and #2. Therefore, the coding rate in the erasurecorrection block in this case is 2/3 and is not the same as fixed codingrate 3/5 in the other erasure correction blocks. That is, as shown inFIG. 12, one of the plurality of erasure correction blocks may have acoding rate different from the set coding rate. This is because thenumber of known information packets included in packets bundled whenerasure correction encoding is performed is different.

FIG. 13 is a block diagram illustrating an example a detailedconfiguration of erasure correction decoding related processing section230 of communication apparatus 200 in FIG. 6.

Error detection section 231 receives decoded packet 301 of the errorcorrection code in the physical layer as input, performs error detectionusing, for example, a CRC check, assigns packet numbers to informationpackets without packet erasure and parity packets without packet erasureand outputs those packets as packet 303.

Known information packet insertion section 232 receives controlinformation 311 including information of the coding rate set for erasurecorrection, packet 303 (information packet without packet erasure (withpacket number assigned) and parity packet without packet erasure (withpacket number assigned)) as input and inserts known information packetsincluded in control information 311 and inserted by the communicatingparty for erasure correction based on information on the set coding rateof the erasure correction code into packet 303. Therefore, knowninformation packet insertion section 232 outputs packet 305 afterinserting the known information packet. Here, control information 311including the information of the coding rate set for erasure correctionis obtained by receiving apparatus 150 in FIG. 6 demodulating thecontrol information symbol shown in FIG. 12.

Erasure correction decoding section 233 receives packet 305 as input,also receives control information 311 including the information of thecoding rate set for erasure correction as input, performs reordering ofpacket 305, that is, reordering of information packets without packeterasure (with packet numbers assigned), parity packets without packeterasure (with packet numbers assigned) and data of known informationpackets, performs erasure correction decoding on the reordered data anddecodes information packet 307. Erasure correction decoding section 233outputs decoded information packet 307.

Known information packet deleting section 234 receives decodedinformation packet 307 and control information 311 including theinformation of the coding rate set for erasure correction as input,deletes the known information packets from information packet 307according to the coding rate and outputs information packet 309 afterthe deletion of known information packets.

Thus, packet generation and known packet insertion section 110 isprovided before erasure correction encoding-related processing section120 and packet generation and known packet insertion section 110 insertsknown information packets, and can thereby change the coding rate inerasure correction encoding-related processing section 120 and canthereby improve both transmission efficiency and erasure correctioncapability.

Although a configuration has been described above where encoding section(parity packet generation section) 1212 provides one coding rate of theerasure correction code and erasure correction encoding-relatedprocessing section 120 inserts known information packets to realizeother coding rates, encoding section (parity packet generation section)1212 may provide, for example, a plurality of erasure correction codesto support different coding rates and erasure correctionencoding-related processing section 120 may insert known informationpackets to further support different coding rates. Furthermore, encodingsection (parity packet generation section) 1212 may provide a pluralityof erasure correction codes of different code lengths to support erasurecorrection of long packets and short packets or may insert knowninformation packets into respective erasure correction codes so thaterasure correction encoding-related processing section 120 may changethe coding rate.

Embodiment 2

Embodiment 1 has described the method of making the coding rate of anerasure correction code variable. A case will be described below wherethe method of making the coding rate of the erasure correction codevariable described in Embodiment 1 will be realized using an LDPC-CC(e.g. see Non-Patent Literature 3).

As a premise thereof, the present embodiment will describe an LDPC-CChaving good characteristics first. Embodiment 3 will describe a methodof making the coding rate variable when an LDPC-CC is applied to aphysical layer which will be described in the present embodiment.Embodiment 4 will describe a method of making the coding rate variablewhen the LDPC-CC described in the present embodiment is used for anerasure correction code.

An LDPC-CC is a convolutional code defined by a low-density parity checkmatrix. As an example, FIG. 14 illustrates parity check matrixH^(T)[0,n] of an LDPC-CC of a coding rate of R=112. Here, element h₁^((m))(t) of H^(T)[0,n] has a value of 0 or 1. All elements other thanh₁ ^((m))(t) are 0. M represents the LDPC-CC memory length, and nrepresents the length of an LDPC-CC codeword. As shown in FIG. 14, acharacteristic of an LDPC-CC parity check matrix is that it is aparallelogram-shaped matrix in which 1 is placed only in diagonal termsof the matrix and neighboring elements, and the bottom-left andtop-right elements of the matrix are zero.

Here, FIG. 15 shows a configuration example of an encoder of LDPC-CCdefined by parity check matrix H^(T)[0,n] when h₁ ⁽⁰⁾(t)=1 and h₂⁽⁰⁾(t)=1. As shown in FIG. 15, the encoder of LDPC-CC is provided with 2(M+1) shift registers 511-1-0 to 511-1-M, 511-2-0 to 511-2-M and a mod 2(exclusive OR) adder 540. For this reason, the encoder of LDPC-CCfeatures the ability to be realized by an extremely simple circuitcompared to a circuit carrying out multiplication of generator matricesor an encoder of LDPC-BC that carries out computations based on abackward (forward) substitution method. Furthermore, since the encodershown in FIG. 15 is an encoder of convolutional code, it is notnecessary to divide an information sequence into blocks of a fixedlength for encoding and an information sequence of an arbitrary lengthcan be encoded.

Hereinafter, an LDPC-CC of a time varying period of g providing goodcharacteristics will be described.

First, an LDPC-CC of a time varying period of 4 having goodcharacteristics will be described. A case in which the coding rate is1/2 will be described below as an example.

Consider equations 1-1 to 1-4 as parity check polynomials of an LDPC-CCfor which the time varying period is 4. At this time, X(D) is apolynomial representation of data (information) and P(D) is a paritypolynomial representation. Here, in equations 1-1 to 1-4, parity checkpolynomials have been assumed in which there are four terms in X(D) andP(D) respectively, the reason being that four terms are desirable fromthe standpoint of obtaining good received quality.[1](D ^(a1) +D ^(a2) +D ^(a3) +D ^(a4))X(D)+(D ^(b1) +D ^(b2) +D ^(b3) +D^(b4))P(D)=0  (Equation 1-1)(D ^(A1) +D ^(A2) +D ^(A3) +D ^(A4))X(D)+(D ^(M) +D ^(B2) +D ^(B3) +D^(B4))P(D)=0  (Equation 1-2)(D ^(a1) +D ^(a2) +D ^(a3) +D ^(a4))X(D)+(D ^(M) +D ^(a2) +D ^(a3) +D^(a4))P(D)=0  (Equation 1-3)(D ^(E1) +D ^(E2) +D ^(E3) +D ^(E4))X(D)+(D ^(F1) +D ^(F2) +D ^(F3) +D^(F4))P(D)=0  (Equation 1-4)

In equation 1-1, it is assumed that a1, a2, a3 and a4 are integers(where a1≠a2≠a3≠a4). Use of the notation “a1≠a2≠a3≠a4” is assumed toexpress the fact that a1, a2, a3 and a4 are all mutually different.Also, it is assumed that b1, b2, b3 and b4 are integers (whereb1≠b2≠b3≠b4). A parity check polynomial of equation 1-1 is called “checkequation #1.” A sub-matrix based on the parity check polynomial ofequation 1-1 is designated first sub-matrix H₁.

In equation 1-2, it is assumed that A1, A2, A3, and A4 are integers(where A1≠A2≠A3≠A4). Also, it is assumed that B1, B2, B3, and B4 areintegers (where B1≠B2≠B3≠B4). A parity check polynomial of equation 1-2is called “check equation #2.” A sub-matrix based on the parity checkpolynomial of equation 1-2 is designated second sub-matrix H₂.

In equation 1-3, it is assumed that α1, α2, α3, and α4 are integers(where α1≠α2≠α3≠α4).

Also, it is assumed that β1, β2, β3, and β4 are integers (whereβ1≠β2≠β3≠β4). A parity check polynomial of equation 1-3 is called “checkequation #3.” A sub-matrix based on the parity check polynomial ofequation 1-3 is designated third sub-matrix H₃.

In equation 1-4, it is assumed that E1, E2, E3, and E4 are integers(where E1≠E2≠E3≠E4). Also, it is assumed that F1, F2, F3, and F4 areintegers (where F1≠F2≠F3≠F4). A parity check polynomial of equation 1-4is called “check equation #4.” A sub-matrix based on the parity checkpolynomial of equation 1-4 is designated fourth sub-matrix H₄.

Next, an LDPC-CC of a time varying period of 4 is considered thatgenerates a parity check matrix such as shown in FIG. 16 from firstsub-matrix H₁, second sub-matrix H₂, third sub-matrix H₃, and fourthsub-matrix H₄.

At this time, if k is designated as a remainder after dividing thevalues of combinations of degrees of X(D) and P(D), (a1, a2, a3, a4),(b1, b2, b3, b4). (A1, A2, A3, A4), (B1, B2, B3, B4), (α1, α2, α3, α4),(β1, β2, β3, β4), (E1, E2, E3, E4), (F1, F2, F3, F4), in equations 1-1to 1-4 by 4, provision is made for one each of remainders 0, 1, 2, and 3to be included in four-coefficient sets represented as shown above (forexample, (a1, a2, a3, a4)), and to hold true with respect to all of theabove four-coefficient sets.

For example, if degrees (a1, a2, a3, a4) of X(D) of “check equation #1”are set as (a1, a2, a3, a4)=(8, 7, 6, 5), remainders k after dividingdegrees (a1, a2, a3, a4) by 4 are (0, 3, 2, 1), and one each of 0, 1, 2and 3 are included in the four-coefficient set as remainders k.Similarly, if degrees (b1, b2, b3, b4) of P(D) of “check equation #1”are set as (b1, b2, b3, b4)=(4, 3, 2, 1), remainders k after dividingdegrees (b1, b2, b3, b4) by 4 are (0, 3, 2, 1), and one each of 0, 1, 2and 3 are included in the four-coefficient set as remainders k. It isassumed that the above condition about “remainder” also holds true forthe four-coefficient sets of X(D) and P(D) of the other parity checkequations (“check equation #2,” “check equation #3” and “check equation#4”).

By this means, the column weight of parity check matrix H configuredfrom equations 1-1 to 1-4 becomes 4 for all columns, which enables aregular LDPC code to be formed. Here, a regular LDPC code is an LDPCcode that is defined by a parity check matrix for which each columnweight is equally fixed, and is characterized by the fact that itscharacteristics are stable and an error floor is unlikely to occur. Inparticular, since the characteristics are good when the column weight is4, an LDPC-CC offering good reception performance can be obtained bygenerating an LDPC-CC as described above.

In the above description, a case in which the coding rate is 1/2 hasbeen described as an example, but a regular LDPC code is also formed andgood received quality can be obtained when the coding rate is (n−1)/n ifthe above condition about “remainder” holds true for four-coefficientsets in information X₁(D), X₂(D), . . . , X_(n−1)(D).

In the case of a time varying period of 2, also, it has been confirmedthat a code with good characteristics can be found if the abovecondition about “remainder” is applied. An LDPC-CC of a time varyingperiod of 2 with good characteristics is described below. A case inwhich the coding rate is 1/2 is described below as an example.

Consider equations 2-1 and 2-2 as parity check polynomials of an LDPC-CCfor which the time varying period is 2. At this time, X(D) is apolynomial representation of data (information) and P(D) is a paritypolynomial representation. Here, in equations 2-1 and 2-2, parity checkpolynomials have been assumed in which there are four terms in X(D) andP(D) respectively, the reason being that four terms are desirable fromthe standpoint of obtaining good received quality.[2](D ^(a1) +D ^(a2) +D ^(a3) +D ^(a4))X(D)+(D ^(b1) +D ^(b2) +D ^(b3) +D^(b4))P(D)=0  (Equation 2-1)(D ^(A1) +D ^(A2) +D ^(A3) +D ^(A4))X(D)+(D ^(B1) +D ^(B2) +D ^(B3) +D^(B4))P(D)=0  (Equation 2-2)

In equation 2-1, it is assumed that a1, a2, a3, and a4 are integers(where a1≠a2≠a3≠a4). Also, it is assumed that b1, b2, b3, and b4 areintegers (where b1≠b2≠b3≠b4). A parity check polynomial of equation 2-1is called “check equation #1.” A sub-matrix based on the parity checkpolynomial of equation 2-1 is designated first sub-matrix H₁.

Furthermore, suppose A1, A2, A3 and A4 in equation 2-2 are integers(where A1≠A2≠A3≠A4). Furthermore, suppose B1, B2, B3 and B4 are integers(where B1≠B2≠B3≠B4). The parity check polynomial of equation 2-2 iscalled “check equation #2.” Suppose the sub-matrix based on the paritycheck polynomial of equation 2-2 is second sub-matrix H₂.

Next, an LDPC-CC of a time varying period of 2 generated from firstsub-matrix H₁ and second sub-matrix H₂ is considered.

At this time, if k is designated as a remainder after dividing thevalues of combinations of degrees of X(D) and P(D), (a1, a2, a3, a4),(b1, b2, b3, b4), (A1, A2, A3, A4), (B1, B2, B3, B4), in equations 2-1and 2-2 by 4, provision is made for one each of remainders 0, 1, 2, and3 to be included in four-coefficient sets represented as shown above(for example, (a1, a2, a3, a4)), and to hold true with respect to all ofthe above four-coefficient sets.

For example, if degrees (a1, a2, a3, a4) of X(D) of “check equation #1”are set as (a1, a2, a3, a4)=(8, 7, 6, 5), remainders k after dividingdegrees (a1, a2, a3, a4) by 4 are (0, 3, 2, 1), and one each of 0, 1, 2and 3 are included in the four-coefficient set as remainders k.Similarly, if degrees (b1, b2, b3, b4) of P(D) of “check equation #1”are set as (b1, b2, b3, b4)=(4, 3, 2, 1), remainders k after dividingdegrees (b1, b2, b3, b4) by 4 are (0, 3, 2, 1), and one each of 0, 1, 2and 3 are included in the four-coefficient set as remainders k. It isassumed that the above condition about “remainder” also holds true forthe four-coefficient sets of X(D) and P(D) of “check equation #2.”

By this means, the column weight of parity check matrix H configuredfrom equations 2-1 and 2-2 becomes 4 for all columns, which enables aregular LDPC code to be formed. Here, a regular LDPC code is an LDPCcode that is defined by a parity check matrix for which each columnweight is equally fixed, and is characterized by the fact that itscharacteristics are stable and an error floor is unlikely to occur. Inparticular, since the characteristics are good when the column weight is8, an LDPC-CC enabling reception performance to be further improved canbe obtained by generating an LDPC-CC as described above.

In the above description (LDPC-CCs of a time varying period of 2), acase in which the coding rate is 1/2 has been described as an example,but a regular LDPC code is also formed and good received quality can beobtained when the coding rate is (n−1)/n if the above condition about“remainder” holds true for four-coefficient sets in information X₁(D),X₂(D), . . . , X_(n−1)(D).

In the case of a time varying period of 3, also, it has been confirmedthat a code with good characteristics can be found if the followingcondition about “remainder” is applied. An LDPC-CC of a time varyingperiod of 3 with good characteristics is described below. A case inwhich the coding rate is 1/2 is described below as an example.

Consider equations 3-1 to 3-3 as parity check polynomials of an LDPC-CCfor which the time varying period is 3. At this time, X(D) is apolynomial representation of data (information) and P(D) is a paritypolynomial representation. Here, in equations 3-1 to 3-3, parity checkpolynomials are assumed such that there are three terms in X(D) and P(D)respectively.[3](D ^(a1) +D ^(a2) +D ^(a3))X(D)+(D ^(b1) +D ^(b2) +D^(b3)+)P(D)=0  (Equation 3-1)(D ^(A1) +D ^(A2) +D ^(A3))X(D)+(D ^(B1) +D ^(B2) +D^(B3))P(D)=0  (Equation 3-2)(D ^(a1) +D ^(a2) +D ^(a3))X(D)+(D ^(B1) +D ^(B2) +D^(B3))P(D)=0  (Equation 3-3)

In equation 3-1, it is assumed that a1, a2, and a3 are integers (wherea1≠a2≠a3). Also, it is assumed that b1, b2 and b3 are integers (whereb1≠b2≠b3). A parity check polynomial of equation 3-1 is called “checkequation #1.” A sub-matrix based on the parity check polynomial ofequation 3-1 is designated first sub-matrix H₁.

In equation 3-2, it is assumed that A1. A2 and A3 are integers (whereA1≠A2≠A3). Also, it is assumed that B1, B2 and B3 are integers (whereB1≠B2≠B3). A parity check polynomial of equation 3-2 is called “checkequation #2.” A sub-matrix based on the parity check polynomial ofequation 3-2 is designated second sub-matrix H₂.

In equation 3-3, it is assumed that α1, α2 and α3 are integers (whereα1≠α2≠α3). Also, it is assumed that β1, β2 and β3 are integers (whereβ1≠β2≠β3). A parity check polynomial of equation 3-3 is called “checkequation #3.” A sub-matrix based on the parity check polynomial ofequation 3-3 is designated third sub-matrix H₃.

Next, an LDPC-CC of a time varying period of 3 generated from firstsub-matrix H₁, second sub-matrix H₂ and third sub-matrix H₃ isconsidered.

At this time, if k is designated as a remainder after dividing thevalues of combinations of degrees of X(D) and P(D), (a1, a2, a3), (b1,b2, b3), (A1, A2, A3), (B1, B2, B3), (α1, α2, α3), (β1, β2, β3), inequations 3-1 to 3-3 by 3, provision is made for one each of remainders0, 1, and 2 to be included in three-coefficient sets represented asshown above (for example, (a1, a2, a3)), and to hold true with respectto all of the above three-coefficient sets.

For example, if degrees (a1, a2, a3) of X(D) of “check equation #1” areset as (a1, a2, a3)=(6, 5, 4), remainders k after dividing degrees (a1,a2, a3) by 3 are (0, 2, 1), and one each of 0, 1, 2 are included in thethree-coefficient set as remainders k. Similarly, if degrees (b1, b2,b3) of P(D) of “check equation #1” are set as (b1, b2, b3)=(3, 2, 1),remainders k after dividing degrees (b1, b2, b3) by 3 are (0, 2, 1), andone each of 0, 1, 2 are included in the three-coefficient set asremainders k. It is assumed that the above condition about “remainder”also holds true for the three-coefficient sets of X(D) and P(D) of“check equation #2” and “check equation #3.”

By generating an LDPC-CC as above, it is possible to generate a regularLDPC-CC code in which the row weight is equal in all rows and the columnweight is equal in all rows with some exceptions (“exceptions” refer topart in the beginning of a parity check matrix and part in the end ofthe parity check matrix, where the row weights and columns weights arenot the same as row weights and column weights of the other part).

Furthermore, when BP decoding is performed, belief in “check equation#2” and belief in “check equation #3” are propagated accurately to“check equation #1,” belief in “check equation #1” and belief in “checkequation #3” are propagated accurately to “check equation #2,” andbelief in “check equation #1” and belief in “check equation #2” arepropagated accurately to “check equation #3.” Consequently, an LDPC-CCwith better received quality can be obtained. This is because, whenconsidered in column units, positions at which “1” is present arearranged so as to propagate belief accurately, as described above.

Hereinafter, the above-described belief propagation will be describedwith the accompanying drawings. FIG. 17A shows parity check polynomialsof an LDPC-CC of a time varying period of 3 and the configuration ofparity check matrix H of this LDPC-CC.

“Check equation #1” illustrates a case in which (a1, a2, a3)=(2, 1, 0)and (b1, b2, b3)=(2, 1, 0) in a parity check polynomial of equation 3-1,and remainders after dividing the coefficients by 3 are as follows:(a1%3, a2%3, a3%3)=(2, 1, 0), (b1%3, b2%3, b3%3)=(2, 1, 0), where “Z %3”represents a remainder after dividing Z by 3.

“Check equation #2” illustrates a case in which (A1, A2, A3)=(5, 1, 0)and (B1, B2, B3)=(5, 1, 0) in a parity check polynomial of equation 3-2,and remainders after dividing the coefficients by 3 are as follows:(A1%3, A2%3, A3%3)=(2, 1, 0), (B1%3, B2%3, B3%3)=(2, 1, 0).

“Check equation #3” illustrates a case in which (α1, α2, α3)=(4, 2, 0)and (β1, β2, β3)=(4, 2, 0) in a parity check polynomial of equation 3-3,and remainders after dividing the coefficients by 3 are as follows:(α1%3, α2%3, α3%3)=(1, 2, 0), (β1%3, β2%3, β3%3)=(1, 2, 0).

Therefore, the example of LDPC-CC of a time varying period of 3 shown inFIG. 17A satisfies the above condition about “remainder,” that is, acondition that (a1%3, a2%3, a3%3), (b1%3, b2%3, b3%3), (A1%3, A2%3,A3%3), (B1%3, B2%3, B3%3), (α1%3, α2%3, α3%3) and (β1%3, β2%3, β3%3) areany of the following: (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0,1), (2, 1, 0).

Returning to FIG. 17A again, belief propagation will now be explained.By column computation of column 6506 in BP decoding, for “1” of area6501 of “check equation #1,” belief is propagated from “1” of area 6504of “check equation #2” and from “1” of area 6505 of “check equation #3.”As described above, “1” of area 6501 of “check equation #1” is acoefficient for which a remainder after division by 3 is 0 (a3%3=0(a3=0) or b3%3=0 (b3=0)). Also, “1” of area 6504 of “check equation #2”is a coefficient for which a remainder after division by 3 is 1 (A2%3=1(A2=1) or B2%3=1 (B2=1)). Furthermore, “1” of area 6505 of “checkequation #3” is a coefficient for which a remainder after division by 3is 2 (α2%3=2 (α2=2) or β2%3=2 (β2=2)).

Thus, for “1” of area 6501 for which a remainder is 0 in thecoefficients of “check equation #1,” in column computation of column6506 in BP decoding, belief is propagated from “1” of area 6504 forwhich a remainder is 1 in the coefficients of “check equation #2” andfrom “1” of area 6505 for which a remainder is 2 in the coefficients of“check equation #3.”

Similarly, for “1” of area 6502 for which a remainder is 1 in thecoefficients of “check equation #1,” in column computation of column6509 in BP decoding, belief is propagated from “1” of area 6507 forwhich a remainder is 2 in the coefficients of “check equation #2” andfrom “1” of area 6508 for which a remainder is 0 in the coefficients of“check equation #3.”

Similarly, for “1” of area 6503 for which a remainder is 2 in thecoefficients of “check equation #1,” in column computation of column6512 in BP decoding, belief is propagated from “I” of area 6510 forwhich a remainder is 0 in the coefficients of “check equation #2” andfrom “1” of area 6511 for which a remainder is 1 in the coefficients of“check equation #3.”

A supplementary explanation of belief propagation will now be givenusing FIG. 17B. FIG. 17B shows the belief propagation relationship ofterms relating to X(D) of “check equation #1” to “check equation #3” inFIG. 17A. “Check equation #1” to “check equation #3” in FIG. 17Aillustrate cases in which (a1, a2, a3)=(2, 1, 0), (A1, A2, A3)=(5, 1,0). and (α1, α2, α3)=(4, 2, 0), in terms relating to X(D) of equations3-1 to 3-3.

In FIG. 17B, terms (a3, A3, α3) inside squares indicate coefficients forwhich a remainder after division by 3 is 0. Furthermore, terms (a2, A2,α1) inside circles indicate coefficients for which a remainder afterdivision by 3 is 1. Furthermore, terms (a1, A1, α2) insidediamond-shaped boxes indicate coefficients for which a remainder afterdivision by 3 is 2.

As can be seen from FIG. 17B, for a1 of “check equation #1,” belief ispropagated from A3 of “check equation #2” and from α1 of “check equation#3” for which remainders after division by 3 differ; For a2 of “checkequation #1,” belief is propagated from A1 of “check equation #2” andfrom α3 of “check equation #3” for which remainders after division by 3differ. For a3 of “check equation #1,” belief is propagated from A2 of“check equation #2” and from α2 of “check equation #3” for whichremainders after division by 3 differ. While FIG. 17B shows the beliefpropagation relationship of terms relating to X(D) of “check equation#1” to “check equation #3,” the same applies to terms relating to P(D).

Thus, for “check equation #1,” belief is propagated from coefficientsfor which remainders after division by 3 are 0, 1, and 2 amongcoefficients of “check equation #2.” That is to say, for “check equation#1,” belief is propagated from coefficients for which remainders afterdivision by 3 are all different among coefficients of “check equation#2.” Therefore, beliefs with low correlation are all propagated to“check equation #1.”

Similarly, for “check equation #2,” belief is propagated fromcoefficients for which remainders after division by 3 are 0, 1, and 2among coefficients of “check equation #1.” That is to say, for “checkequation #2,” belief is propagated from coefficients for whichremainders after division by 3 are all different among coefficients of“check equation #1.” Also, for “check equation #2,” belief is propagatedfrom coefficients for which remainders after division by 3 are 0, 1, and2 among coefficients of “check equation #3.” That is to say, for “checkequation #2,” belief is propagated from coefficients for whichremainders after division by 3 are all different among coefficients of“check equation #3.”

Similarly, for “check equation #3,” belief is propagated fromcoefficients for which remainders after division by 3 are 0, 1, and 2among coefficients of “check equation #1.” That is to say, for “checkequation #3,” belief is propagated from coefficients for whichremainders after division by 3 are all different among coefficients of“check equation #1.” Also, for “check equation #3,” belief is propagatedfrom coefficients for which remainders after division by 3 are 0, 1, and2 among coefficients of “check equation #2.” That is to say, for “checkequation #3,” belief is propagated from coefficients for whichremainders after division by 3 are all different among coefficients of“check equation #2.”

By providing for the degrees of parity check polynomials of equations3-1 to 3-3 to satisfy the above condition about “remainder” in this way,belief is necessarily propagated in all column computations. so that itis possible to perform belief propagation efficiently in all checkequations and further increase error correction capability.

A case in which the coding rate is 1/2 has been described above for anLDPC-CC of a time varying period of 3, but the coding rate is notlimited to 1/2. A regular LDPC code is also formed and good receivedquality can be obtained when the coding rate is (n−1)/n (where n is aninteger equal to or greater than 2) if the above condition about“remainder” holds true for three-coefficient sets in information X₁(D),X₂(D), . . . , X_(n−1)(D).

A case in which the coding rate is (n−1)/n (where n is an integer equalto or greater than 2) is described below.

Consider equations 4-1 to 4-3 as parity check polynomials of an LDPC-CCfor which the time varying period is 3. At this time, X₁(D), X₂(D), . .. , X_(n−1)(D) are polynomial representations of data (information) X₁,X₂, . . . , X_(n−1), and P(D) is a parity polynomial representation.Here, in equations 4-1 to 4-3, parity check polynomials are assumed suchthat there are three terms in X₁(D), X₂(D), . . . , X_(n−1)(D) and P(D)respectively.[4](D ^(a1,1) +D ^(a1,2) +D ^(a1,3))X ₁(D)+(D ^(a2,1) +D ^(a2,2) +D^(a2,3))X ₂(D)+ . . . +(D ^(an−1,1) +D ^(an−1,2) +D ^(an−1,3)X)_(n−1)(D)+(D ^(b1) +D ^(b2) +D ^(b3))P(D)=0  (Equation 4-1)(D ^(A1,1) +D ^(A1,2) +D ^(A1,3))X ₁(D)+(D ^(A2,1) +D ^(A2,2) +D^(A2,3))X ₂(D)+ . . . +(D ^(An-1,1) +D ^(An-1,2) +D ^(An-1,3)X)_(n−1)(D)+(D ^(H1) +D ^(H2) +D ^(H3))P(D)=0  (Equation 4-2)(D ^(a1,1) +D ^(a1,2) +D ^(a1,3))X ₁(D)+(D ^(a2,1) +D ^(a2,2) +D^(a2,3))X ₂(D)+ . . . +(D ^(an−1,1) +D ^(an−1,2) +D ^(an−1,3)X)_(n−1)(D)+(D ^(B1) +D ^(B2) +D ^(B3))P(D)=0  (Equation 4-3)

In equation 4-1, it is assumed that a_(i,1), a_(i,2), and a_(i,3) (wherei=1, 2, . . . , n−1) are integers (where a_(i,1)≠a_(i,2)≠a_(i,3)). Also,it is assumed that b1, b2 and b3 are integers (where b1≠b2≠b3). A paritycheck polynomial of equation 4-1 is called “check equation #1.” Asub-matrix based on the parity check polynomial of equation 4-1 isdesignated first sub-matrix H₁.

In equation 4-2, it is assumed that A_(i,1), A_(i,2), and A_(i,3) (wherei=1, 2, . . . , n−1) are integers (where A_(i,1)≠A_(i,2)≠A_(i,3)). Also,it is assumed that B1, B2 and B3 are integers (where B1≠B2≠B3). A paritycheck polynomial of equation 4-2 is called “check equation #2.” Asub-matrix based on the parity check polynomial of equation 4-2 isdesignated second sub-matrix H₂.

In equation 4-3, it is assumed that α_(i,1), α_(i,2), and α_(i,3) (wherei=1, 2, . . . , n−1) are integers (where α_(i,1)≠α_(i,2)≠α_(i,3)). Also,it is assumed that β1, β2 and β3 are integers (where β1≠β2≠β3). A paritycheck polynomial of equation 4-3 is called “check equation #3.” Asub-matrix based on the parity check polynomial of equation 4-3 isdesignated third sub-matrix H₃.

Next, an LDPC-CC of a time varying period of 3 generated from firstsub-matrix H₁, second sub-matrix H₂ and third sub-matrix H₃ isconsidered.

At this time, if k is designated as a remainder after dividing thevalues of combinations of degrees of X₁(D), X₂(D), . . . , X_(n−1)(D),and P(D), (a_(1,1), a_(1,2), a_(1,3)), (a_(2,1), a_(2,2), a_(2,3)), . .. , (a_(n−1,1), a_(n−1,2), a_(n−1,3)). (b1, b2, b3), (A_(1,1), A_(1,2),A_(1,3)), (A_(2,1), A_(2,2), A_(2,3)), . . . , (A_(n−1,1), A_(n−1,2),A_(n−1,3)), (B1, B2, B3), (α_(1,1), α_(1,2), α_(1,3)), (a_(2,1),a_(2,2), a_(2,3)), . . . , (α_(n−1,1), a_(n−1,2), a_(n−1,3)), (β1, β2,β3), in equations 4-1 to 4-3 by 3, provision is made for one each ofremainders 0, 1, and 2 to be included in three-coefficient setsrepresented as shown above (for example, (a_(1,1), a_(1,2). a_(1,3))),and to hold true with respect to all of the above three-coefficientsets.

That is to say, provision is made for (a_(1,1)%3, a_(1,2)%3, a_(1,3)%3),(a_(2,1)%3, a_(2,2)%3, a_(2,3)%3), . . . , (a_(n−1,1)%3, a_(n−1,2)%3,a_(1,3)%3), (b1%3, b2%3, b3%3), (A_(1,1)%3, A_(1,2)%3, A_(1,3)%3),(A_(2,1)%3, A_(2,2)%3, A_(2,3)%3), . . . , (A_(n−1,1)%3, A_(n−1,2)%3,A_(n−1,3)%3), (B1%3, B2%3, B3%3), (α_(1,1)%3, α_(1,2)%3, α_(1,3)%3),(α_(2,1)%3, α_(2,2)%3, α_(2,3)%3), . . . , (α_(n−1,1)%3, α_(n−1,2)%3,α_(n−1,3)%3) and (β1%3, β2%3, β3%3) to be any of the following: (0, 1,2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), (2, 1, 0).

Generating an LDPC-CC in this way enables a regular LDPC-CC code to begenerated. Furthermore, when BP decoding is performed, belief in “checkequation #2” and belief in “check equation #3” are propagated accuratelyto “check equation #1,” belief in “check equation #1” and belief in“check equation #3” are propagated accurately to “check equation #2,”and belief in “check equation #1” and belief in “check equation #2” arepropagated accurately to “check equation #3.” Consequently, an LDPC-CCwith better received quality can be obtained in the same way as in thecase of a coding rate of 1/2.

It has been confirmed that, as in the case of a time varying period of3, a code with good characteristics can be found if the condition about“remainder” below is applied to an LDPC-CC for which the time varyingperiod is a multiple of 3 (for example, 6, 9, 12, . . . ). An LDPC-CC ofa multiple of a time varying period of 3 with good characteristics isdescribed below. The case of an LDPC-CC of a coding rate of 1/2 and atime varying period of 6 is described below as an example.

Consider equations 5-1 to 5-6 as parity check polynomials of an LDPC-CCfor which the time varying period is 6.[5](D ^(a1,1) +D ^(a1,2) +D ^(a1,3))X(D)+(D ^(b1,1) +D ^(b1,2) +D^(b1,3))P(D)=0  (Equation 5-1)(D ^(a2,1) +D ^(a2,2) +D ^(a2,3))X(D)+(D ^(b2,1) +D ^(b2,2) +D^(b2,3))P(D)=0  (Equation 5-2)(D ^(a3,1) +D ^(a3,2) +D ^(a3,3))X(D)+(D ^(b3,1) +D ^(b3,2) +D^(b3,3))P(D)=0  (Equation 5-3)(D ^(a4,1) +D ^(a4,2) +D ^(a4,3))X(D)+(D ^(b4,1) +D ^(b4,2) +D^(b4,3))P(D)=0  (Equation 5-4)(D ^(a5,1) +D ^(a5,2) +D ^(a5,3))X(D)+(D ^(b5,1) +D ^(b5,2) +D^(b5,3))P(D)=0  (Equation 5-5)(D ^(a6,1) +D ^(a6,2) +D ^(a6,3))X(D)+(D ^(b6,1) +D ^(b6,2) +D^(b6,3))P(D)=0  (Equation 5-6)

At this time, X(D) is a polynomial representation of data (information)and P(D) is a parity polynomial representation. With an LDPC-CC of atime varying period of 6, if i %6=k (where k=0, 1, 2, 3, 4, 5) isassumed for parity part Pi and information Xi at time i, a parity checkpolynomial of equation 5−(k+1) holds true. For example, if i=1, i %6=1(k=1), and therefore equation 6 holds true.[6](D ^(a2,1) +D ^(a2,2) +D ^(a2,3))X ₁+(D ^(b2,1) +D ^(b2,2) +D ^(b2,3))P₁=0  (Equation 6)

Here, in equations 5-1 to 5-6, parity check polynomials are assumed suchthat there are three terms in X(D) and P(D) respectively.

In equation 5-1, it is assumed that a1,1, a1,2, a1,3 are integers (wherea1,1≠a1,2≠a1,3). Also, it is assumed that b1,1, b1,2, and b1,3 areintegers (where b1,1≠b1,2≠b1,3). A parity check polynomial of equation5-1 is called “check equation #1.” A sub-matrix based on the paritycheck polynomial of equation 5-1 is designated first sub-matrix H₁.

In equation 5-2, it is assumed that a2,1, a2,2, and a2,3 are integers(where a2,1≠a2,2≠a2,3). Also, it is assumed that b2,1, b2,2, b2,3 areintegers (where b2,1≠b2,2≠b2,3). A parity check polynomial of equation5-2 is called “check equation #2.” A sub-matrix based on the paritycheck polynomial of equation 5-2 is designated second sub-matrix H₂.

In equation 5-3, it is assumed that a3,1, a3,2, and a3,3 are integers(where a3,1≠a3,2≠a3,3). Also, it is assumed that b3,1, b3,2, and b3,3are integers (where b3,11≠b3,2≠b3,3). A parity check polynomial ofequation 5-3 is called “check equation #3.” A sub-matrix based on theparity check polynomial of equation 5-3 is designated third sub-matrixH₃.

In equation 5-4, it is assumed that a4,1, a4,2, and a4,3 are integers(where a4,1≠a4,2≠a4,3). Also, it is assumed that b4,1, b4,2, and b4,3are integers (where b4,1≠b4,2≠b4,3). A parity check polynomial ofequation 5-4 is called “check equation #4.” A sub-matrix based on theparity check polynomial of equation 5-4 is designated fourth sub-matrixHA.

In equation 5-5, it is assumed that a5,1, a5,2, and a5,3 are integers(where a5,1≠a5,2≠a5,3). Also, it is assumed that b5,1, b5,2, and b5,3are integers (where b5,1≠b5,2≠b5,3). A parity check polynomial ofequation 5-5 is called “check equation #5.” A sub-matrix based on theparity check polynomial of equation 5-5 is designated fifth sub-matrixH₅.

In equation 5-6, it is assumed that a6,1, a6,2, and a6,3 are integers(where a6,1≠a6,2≠a6,3). Also, it is assumed that b6,1. b6,2, and b6,3are integers (where b6,1≠b6,2≠b6,3). A parity check polynomial ofequation 5-6 is called “check equation #6.” A sub-matrix based on theparity check polynomial of equation 5-6 is designated sixth sub-matrixH₆.

Next, an LDPC-CC of a time varying period of 6 is considered that isgenerated from first sub-matrix H₁, second sub-matrix H₂, thirdsub-matrix H₃, fourth sub-matrix H₄, fifth sub-matrix H₅ and sixthsub-matrix H₆.

At this time, if k is designated as a remainder after dividing thevalues of combinations of degrees of X(D) and P(D), (a1,1, a1,2, a1,3),(b1,1, b1,2, b1,3), (a2,1, a2,2, a2,3), (b2,1, b2,2, b2,3), (a3,1, a3,2,a3,3), (b3,1, b3,2, b3,3), (a4,1, a4,2, a4,3), (b4,1, b4,2, b4,3),(a5,1, a5,2, a5,3), (b5,1, b5,2, b5,3), (a6,1, a6,2, a6,3), (b6,1, b6,2,b6,3), in equations 5-1 to 5-6 by 3, provision is made for one each ofremainders 0, 1, and 2 to be included in three-coefficient setsrepresented as shown above (for example, (a1,1, a1,2, a1,3)), and tohold true with respect to all of the above three-coefficient sets. Thatis to say, provision is made for (a1,1%3, a1,2%3, a1,3%3), (b1,1%3,b1,2%3, b1,3%3), (a2,1%3, a2,2%3, a2,3%3), (b2,1%3, b2,2%3, b2,3%3),(a3,1%3, a3,2%3, a3,3%3), (b3,1%3, b3,2%3, b3,3%3), (a4,1%3, a4,2%3,a4,3%3), (b4,1%3, b4,2%3, b4,3%3), (a5,1%3, a5,2%3, a5,3%3), (b5,1%3,b5,2%3, b5,3%3), (a6,1%3, a6,2%3, a6,3%3) and (b6,1%3, b6,2%3, b6,3%3)to be any of the following: (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0),(2, 0, 1), (2, 1, 0).

By generating an LDPC-CC in this way, if an edge is present when aTanner graph is drawn for “check equation #1,” belief in “check equation#2 or check equation #5” and belief in “check equation #3 or checkequation #6” are propagated accurately.

Also, if an edge is present when a Tanner graph is drawn for “checkequation #2,” belief in “check equation #1 or check equation #4” andbelief in “check equation #3 or check equation #6” are propagatedaccurately.

If an edge is present when a Tanner graph is drawn for “check equation#3,” belief in “check equation #1 or check equation #4” and belief in“check equation #2 or check equation #5” are propagated accurately. Ifan edge is present when a Tanner graph is drawn for “check equation #4,”belief in “check equation #2 or check equation #5” and belief in “checkequation #3 or check equation #6” are propagated accurately.

If an edge is present when a Tanner graph is drawn for “check equation#5,” belief in “check equation #1 or check equation #4” and belief in“check equation #3 or check equation #6” are propagated accurately. Ifan edge is present when a Tanner graph is drawn for “check equation #6,”belief in “check equation #1 or check equation #4” and belief in “checkequation #2 or check equation #5” are propagated accurately.

Consequently, an LDPC-CC of a time varying period of 6 can maintainbetter error correction capability in the same way as when the timevarying period is 3.

In this regard, belief propagation will be described using FIG. 17C.FIG. 17C shows the belief propagation relationship of terms relating toX(D) of “check equation #1” to “check equation #6.” In FIG. 17C, asquare indicates a coefficient for which a remainder after division by 3in ax,y (where x=1, 2, 3, 4, 5, 6, and y=1, 2, 3) is 0.

A circle indicates a coefficient for which a remainder after division by3 in ax,y (where x=1, 2, 3, 4, 5, 6, and y=1, 2, 3) is 1. Adiamond-shaped box indicates a coefficient for which a remainder afterdivision by 3 in ax,y (where x=1, 2, 3, 4, 5, 6, and y=1, 2, 3) is 2.

As can be seen from FIG. 17C, if an edge is present when a Tanner graphis drawn, for a1,1 of “check equation #1,” belief is propagated from“check equation #2 or #5” and “check equation #3 or #6” for whichremainders after division by 3 differ. Similarly, if an edge is presentwhen a Tanner graph is drawn, for a1,2 of “check equation #1,” belief ispropagated from “check equation #2 or #5” and “check equation #3 or #6”for which remainders after division by 3 differ.

Similarly, if an edge is present when a Tanner graph is drawn, for a1,3of “check equation #1,” belief is propagated from “check equation #2 or#5” and “check equation #3 or #6” for which remainders after division by3 differ. While FIG. 17C shows the belief propagation relationship ofterms relating to X(D) of “check equation #1” to “check equation #6,”the same applies to terms relating to P(D).

Thus, belief is propagated to each node in a Tanner graph of “checkequation #1” from coefficient nodes of other than “check equation #1.”Therefore, beliefs with low correlation are all propagated to “checkequation #1,” enabling an improvement in error correction capability tobe expected.

In FIG. 17C. “check equation #1” has been focused upon, but a Tannergraph can be drawn in a similar way for “check equation #2” to “checkequation #6,” and belief is propagated to each node in a Tanner graph of“check equation #K” from coefficient nodes of other than “check equation#K.” Therefore, beliefs with low correlation are all propagated to“check equation #K” (where K=2, 3, 4, 5, 6), enabling an improvement inerror correction capability to be expected.

By providing for the degrees of parity check polynomials of equations5-1 to 5-6 to satisfy the above condition about “remainder” in this way,belief can be propagated efficiently in all check equations, and thepossibility of being able to further improve error correction capabilityis increased.

A case in which the coding rate is 1/2 has been described above for anLDPC-CC of a time varying period of 6, but the coding rate is notlimited to 1/2. The possibility of obtaining good received quality canbe increased when the coding rate is (n−1)/n (where n is an integerequal to or greater than 2) if the above condition about “remainder”holds true for three-coefficient sets in information X₁(D), X₂(D), . . ., X_(n−1)(D).

A case in which the coding rate is (n−1)/n (where n is an integer equalto or greater than 2) is described below.

Consider equations 7-1 to 7-6 as parity check polynomials of an LDPC-CCfor which the time varying period is 6.[7](D ^(a#1,1,1) +D ^(a#1,1,2) +D ^(a#1,1,3))X ₁(D)+(D ^(a#1,2,1) +D^(a#1,2,2) +D ^(a#1,2,3))X ₂(D)+ . . . +(D ^(a#1,n-1,1) +D ^(a#1,n-1,2)+D ^(a#1,n-1,3))X _(n−1)(D)+(D ^(b#1,1) +D ^(b#1,2) +D^(b#1,3))P(D)=0  (Equation 7-1)(D ^(a#2,1,1) +D ^(a#2,1,2) +D ^(a#2,1,3))X ₁(D)+(D ^(a#2,2,1) +D^(a#2,2,2) +D ^(a#2,2,3))X ₂(D)+ . . . +(D ^(a#2,n-1,1) +D ^(a#2,n-1,2)+D ^(a#2,n-1,3))X _(n−1)(D)+(D ^(b#2,1) +D ^(b#2,2) +D^(b#2,3))P(D)=0  (Equation 7-2)(D ^(a#3,1,1) +D ^(a#3,1,2) +D ^(a#3,1,3))X ₁(D)+(D ^(a#3,2,1) +D^(a#3,2,2) +D ^(a#3,2,3))X ₂(D)+ . . . +(D ^(a#3,n-1,1) +D ^(a#3,n-1,2)+D ^(a#3,n-1,3))X _(n−1)(D)+(D ^(b#3,1) +D ^(b#3,2) +D ^(b#3,3))P(D)=0  (Equation 7-3)(D ^(a#4,1,1) +D ^(a#4,1,2) +D ^(a#4,1,3))X ₁(D)+(D ^(a#4,2,1) +D^(a#4,2,2) +D ^(a#4,2,3))X ₂(D)+ . . . +(D ^(a#4,n-1,1) +D ^(a#4,n-1,2)+D ^(a#4,n-1,3))X _(n−1)(D)+(D ^(b#4,1) +D ^(b#4,2) +D ^(b#4,3))P(D)=0  (Equation 7-4)(D ^(a#5,1,1) +D ^(a#5,1,2) +D ^(a#5,1,3))X ₁(D)+(D ^(a#5,2,1) +D^(a#5,2,2) +D ^(a#5,2,3))X ₂(D)+ . . . +(D ^(a#5,n-1,1) +D ^(a#5,n-1,2)+D ^(a#5,n-1,3))X _(n−1)(D)+(D ^(b#5,1) +D ^(b#5,2) +D ^(b#5,3))P(D)=0  (Equation 7-5)(D ^(a#6,1,1) +D ^(a#6,1,2) +D ^(a#6,1,3))X ₁(D)+(D ^(a#6,2,1) +D^(a#6,2,2) +D ^(a#6,2,3))X ₂(D)+ . . . +(D ^(a#6,n-1,1) +D ^(a#6,n-1,2)+D ^(a#6,n-1,3))X _(n−1)(D)+(D ^(b#6,1) +D ^(b#6,2) +D ^(b#6,3))P(D)=0  (Equation 7-6)

At this time, X₁(D), X₂(D), . . . , X_(n−1)(D) are polynomialrepresentations of data (information) X₁, X₂, . . . , Xn−1, and P(D) isa parity polynomial representation. Here, in equations 7-1 to 7-6,parity check polynomials are assumed such that there are three terms inX₁(D), X₂(D), . . . , X_(n−1)(D), and P(D) respectively. As in the caseof the above coding rate of 1/2, and in the case of a time varyingperiod of 3, the possibility of being able to obtain higher errorcorrection capability is increased if the condition below (<Condition#1>) is satisfied in an LDPC-CC of a time varying period of 6 and acoding rate of (n−1)/n (where n is an integer equal to or greater than2) represented by parity check polynomials of equations 7-1 to 7-6.

In an LDPC-CC of a time varying period of 6 and a coding rate of (n−1)/n(where n is an integer equal to or greater than 2), the parity part andinformation at time i are represented by Pi and X_(i,1), X_(i,2), . . ., X_(i,n−1) respectively. If i %6=k (where k=0, 1, 2, 3, 4, 5) isassumed at this time, a parity check polynomial of equation 7−(k+1)holds true. For example, if i=8, i %6=2 (k=2), and therefore equation 8holds true.[8](D ^(a#3,1,1) +D ^(a#3,1,2) +D ^(a#3,1,3))X _(8,1)+(D ^(a#3,2,1) +D^(a#3,2,2) +D ^(a#3,2,3))X _(8,2)+ . . . +(D ^(a#3,n-1,1) +D^(a#3,n-1,2) +D ^(a#3,n-1,3))X _(8,n−1)+(D ^(b#3,1) +D ^(b#3,2) +D^(b#3,3))P ₈=0  (Equation 8)

<Condition #1>

In equations 7-1 to 7-6, combinations of degrees of X₁(D), X₂(D), . . ., X_(n−1)(D), and P(D) satisfy the following condition:

(a_(#1,1,1)%3, a_(#1,1,2)%3, a_(#1,1,3)%3), (a_(#1,2,1)%3, a#1,2,2%3,a_(#1,2,3)%3), . . . , (a_(#1,k,1)%3, a_(#1,k,2)%3, a_(#1,k,3)%3), . . ., (a_(#1,n−1,1)%3, a_(#1,n−1,2)%3, a_(#1,n−1,3)%3) and (b_(#1,1)%3,b_(#1,2)%3, b_(#1,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1,2, 0), (2, 0, 1), or (2, 1, 0) (where k=1, 2, 3, . . . , n−1);

(a_(#2,1,1)%3, a_(#2,1,2)%3, a_(#2,1,3)%3), (a_(#2,2,1)%3, a_(#2,2,2)%3,a_(#2,2,3)%3), . . . , (a_(#2,k,1)%3, a_(#2,k,2)%3, a_(#2,k,3)%3), . . ., (a_(#2,n−1,1)%3, a_(#2,n−1,2)%3, a_(#2,n−1,3)%3) and (b_(#2,1)%3,b_(#2,2)%3, b_(#2,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1,2, 0), (2, 0, 1), or (2, 1, 0) (where k=1, 2, 3, . . . , n−1);

(a_(#3,1,1)%3, a_(#3,1,2)%3, a_(#3,1,3)%3), (a_(#3,2,1)%3, a_(#3,2,2)%3,a_(#3,2,3)%3), . . . , (a_(#3,k,1)%3, a_(#3,k,2)%3, a_(#3,k,3)%3), . . ., (a_(#3,n−1,1)%3, a_(#3,n−1,2)%3, a_(#3,n−1,3)%3) and (b_(#3,1)%3,b_(#3,2)%3, b_(#3,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2),(1, 2, 0), (2, 0, 1), or (2, 1, 0) (where k=1, 2, 3, . . . , n−1);

(a_(#4,1,1)%3, a_(#4,1,2)%3, a_(#4,1,3)%3), (a_(#4,2,1)%3, a_(#4,2,2)%3,a_(#4,2,3)%3), . . . , (a_(#4,k,1)%3, a_(#4,k,2)%3, a_(#4,k,3)%3), . . ., (a_(#4,n−1,1)%3, a_(#4,n−1,2)%3, a_(#4,n−1,3)%3) and (b_(#4,1)%3,b_(#4,2)%3, b_(#4,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2),(1, 2, 0), (2, 0, 1), or (2, 1, 0) (where k=1, 2, 3, . . . , n−1);

(a_(#5,1,1)%3, a_(#5,1,2)%3, a_(#5,1,3)%3), (a_(#5,2,1)%3, a_(#5,2,2)%3,a_(#5,2,3)%3), . . . , (a_(#5,k,1)%3, a_(#5,k,2)%3, a_(#5,k,3)%3), . . ., (a_(#5,n−1,1)%3, a_(#5,n−1,2)%3, a_(#5,n−1,3)%3) and (b_(#5,1)%3,b_(#5,2)%3, b_(#5,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2),(1, 2, 0), (2, 0, 1), or (2, 1, 0) (where k=1, 2, 3, . . . , n−1); and

(a_(#6,1,1)%3, a_(#6,1,2)%3, a_(#6,1,3)%3), (a_(#6,2,1)%3, a_(#6,2,2)%3,a_(#6,2,3)%3), . . . , (a_(#6,k,1)%3, a_(#6,k,2)%3, a_(#6,k,3)%3), . . ., (a_(#6,n−1,1)%3, a_(#6,n−1,2)%3, a_(#6,n−1,3)%3) and (b_(#6,1)%3,b_(#6,2)%3, b_(#6,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2),(1, 2, 0), (2, 0, 1), or (2, 1, 0) (where k=1, 2, 3, . . . , n−1);

In the above description, a code having high error correction capabilityhas been described for an LDPC-CC of a time varying period of 6, but acode having high error correction capability can also be generated whenan LDPC-CC of a time varying period of 3g (where g=1, 2, 3, 4, . . . )(that is, an LDPC-CC for which the time varying period is a multiple of3) is created in the same way as with the design method for an LDPC-CCof a time varying period of 3 or 6. A configuration method for this codeis described in detail below.

Consider equations 9-1 to 9-3g as parity check polynomials of an LDPC-CCfor which the time varying period is 3g (where g=1, 2, 3, 4, . . . ) andthe coding rate is (n−1)/n (where n is an integer equal to or greaterthan 2).

$\begin{matrix}{\mspace{79mu}\lbrack 9\rbrack} & \; \\{{{\left( {D^{{a{\# 1}},1,1} + D^{{a{\# 1}},1,2} + D^{{a{\# 1}},1,3}} \right){X_{1}(D)}} + {\left( {D^{{a{\# 1}},2,1} + D^{{a{\# 1}},2,2} + D^{{a{\# 1}},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 1}},{n - 1},1} + D^{{a{\# 1}},{n - 1},2} + D^{{a{\# 1}},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 1}},1} + D^{{b{\# 1}},2} + D^{{b{\# 1}},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 9\text{-}1} \right) \\{{{\left( {D^{{a{\# 2}},1,1} + D^{{a{\# 2}},1,2} + D^{{a{\# 2}},1,3}} \right){X_{1}(D)}} + {\left( {D^{{a{\# 2}},2,1} + D^{{a{\# 2}},2,2} + D^{{a{\# 2}},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 2}},{n - 1},1} + D^{{a{\# 2}},{n - 1},2} + D^{{a{\# 2}},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 2}},1} + D^{{b{\# 2}},2} + D^{{b{\# 2}},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 9\text{-}2} \right) \\{{{\left( {D^{{a{\# 3}},1,1} + D^{{a{\# 3}},1,2} + D^{{a{\# 3}},1,3}} \right){X_{1}(D)}} + {\left( {D^{{a{\# 3}},2,1} + D^{{a{\# 3}},2,2} + D^{{a{\# 3}},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 3}},{n - 1},1} + D^{{a{\# 3}},{n - 1},2} + D^{{a{\# 3}},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 3}},1} + D^{{b{\# 3}},2} + D^{{b{\# 3}},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 9\text{-}3} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{a\# k},1,1} + D^{{a\# k},1,2} + D^{{a\# k},1,3}} \right){X_{1}(D)}} + {\left( {D^{{a\# k},2,1} + D^{{a\# k},2,2} + D^{{a\# k},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a\# k},{n - 1},1} + D^{{a\# k},{n - 1},2} + D^{{a\# k},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{b\# k},1} + D^{{b\# k},2} + D^{{b\# k},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 9\text{-}k} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{{a{\# 3}g} - 2},1,1} + D^{{{a{\# 3}g} - 2},1,2} + D^{{{a{\# 3}g} - 2},1,3}} \right){X_{1}(D)}} + {\left( {D^{{{a{\# 3}g} - 2},2,1} + D^{{{a{\# 3}g} - 2},2,2} + D^{{{a{\# 3}g} - 2},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{{a{\# 3}g} - 2},{n - 1},1} + D^{{{a{\# 3}g} - 2},{n - 1},2} + D^{{{a{\# 3}g} - 2},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{{b{\# 3}g} - 2},1} + D^{{{b{\# 3}g} - 2},2} + D^{{{b{\# 3}g} - 2},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 9\text{-}\left( {3g\text{-}2} \right)} \right) \\{{{\left( {D^{{{a{\# 3}g} - 1},1,1} + D^{{{a{\# 3}g} - 1},1,2} + D^{{{a{\# 3}g} - 1},1,3}} \right){X_{1}(D)}} + {\left( {D^{{{a{\# 3}g} - 1},2,1} + D^{{{a{\# 3}g} - 1},2,2} + D^{{{a{\# 3}g} - 1},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{{a{\# 3}g} - 1},{n - 1},1} + D^{{{a{\# 3}g} - 1},{n - 1},2} + D^{{{a{\# 3}g} - 1},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{{b{\# 3}g} - 1},1} + D^{{{b{\# 3}g} - 1},2} + D^{{{b{\# 3}g} - 1},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 9\text{-}\left( {3g\text{-}1} \right)} \right) \\{{{\left( {D^{{a{\# 3}g},1,1} + D^{{a{\# 3}g},1,2} + D^{{a{\# 3}g},1,3}} \right){X_{1}(D)}} + {\left( {D^{{a{\# 3}g},2,1} + D^{{a{\# 3}g},2,2} + D^{{a{\# 3}g},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 3}g},{n - 1},1} + D^{{a{\# 3}g},{n - 1},2} + D^{{a{\# 3}g},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 3}g},1} + D^{{b{\# 3}g},2} + D^{{b{\# 3}g},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 9\text{-}3g} \right)\end{matrix}$

At this time, X₁(D), X₂(D), . . . , X_(n−1)(D) are polynomialrepresentations of data (information) X₁, X₂, . . . , X_(n−1), and P(D)is a parity polynomial representation. Here, in equations 9-1 to 9-3g,parity check polynomials are assumed such that there are three terms inX₁(D), X₂(D), . . . , X_(n−1)(D), and P(D) respectively.

As in the case of an LDPC-CC of a time varying period of 3 and anLDPC-CC of a time varying period of 6, the possibility of being able toobtain higher error correction capability is increased if the conditionbelow (<Condition #2>) is satisfied in an LDPC-CC of a time varyingperiod of 3g and a coding rate of (n−1)/n (where n is an integer equalto or greater than 2) represented by parity check polynomials ofequations 9-1 to 9-3g.

In an LDPC-CC of a time varying period of 3g and a coding rate of(n−1)/n (where n is an integer equal to or greater than 2), the paritypart and information at time i are represented by P_(i) and X_(i,1),X_(i,2), . . . , X_(i,n−1). respectively. If i %3g=k (where k=0, 1, 2, .. . , 3g−1) is assumed at this time, a parity check polynomial ofequation 9−(k+1) holds true. For example, if i=2, i %3g=2 (k=2), andtherefore equation 10 holds true.[10](D ^(a#3,1,1) +D ^(a#3,1,2) +D ^(a#3,1,3))X _(2,1)+(D ^(a#3,2,1) +D^(a#3,2,2) +D ^(a#3,2,3))X _(2,2)+ . . . +(D ^(a#3,n-1,1) +D^(a#3,n-1,2) +D ^(a#3,n-1,3))X _(2,n−1)+(D ^(b#3,1) +D ^(b#3,2) +D^(b#3,3))P ₂=0   (Equation 10)

In equations 9-1 to 9-3g, it is assumed that a_(#k,p,1), a_(#k,p,2) anda_(#k,p,3) are integers (where a_(#k,p,1)≠a_(#k,p,2)≠a_(#k,p,3)) (wherek=1, 2, 3, . . . , 3g, and p=1, 2, 3, . . . , n−1). Also, it is assumedthat b_(#k,1), b_(#k,2) and b_(#k,3) are integers (whereb_(#k,1)≠b_(#k,2)≠b_(#k,3)). A parity check polynomial of equation 9-k(where k=1, 2, 3, . . . , 3g) is called “check equation #k.” Asub-matrix based on the parity check polynomial of equation 9-k isdesignated k-th sub-matrix H_(k). Next, an LDPC-CC of a time varyingperiod of 3g is considered that is generated from first sub-matrix H₁,second sub-matrix H₂, third sub-matrix H₃, . . . , and 3g-th sub-matrixH₃.

<Condition #2>

In equations 9-1 to 9-3g, combinations of degrees of X₁(D), X₂(D), . . ., X_(n−1)(D), and P(D) satisfy the following condition:

(a_(#1,1,1)%3, a_(#1,1,2)%3, a_(#1,1,3)%3), (a_(#1,2,1)%3, a_(#1,2,2)%3,a_(#1,2,3)%3), . . . , (a_(#1,p,1)%3, a_(#1,p,2)%3, a_(#1,p,3)%3), . . ., (a_(#1,n−1,1)%3, a_(#1,n−1,2)%3, a_(#1,n−1,3)%3) and (b_(#1,1)%3,b_(#1,2)%3, b_(#1,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2),(1, 2, 0), (2, 0, 1), or (2, 1, 0) (where p=1, 2, 3, . . . , n−1);

(a_(#2,1,1)%3, a_(#2,1,2)%3, a_(#2,1,3)%3), (a_(#2,2,1)%3, a_(#2,2,2)%3,a_(#2,2,3)%3), . . . , (a_(#2,p,1)%3, a_(#2,p,2)%3, a_(#2,p,3)%3), . . ., (a_(#2,n−1,1)%3, a_(#2,n−1,2)%3, a_(#2,n−1,3)%3) and (b_(#2,1)%3,b_(#2,2)%3, b_(#2,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2),(1, 2, 0), (2, 0, 1), or (2, 1, 0) (where p=1, 2, 3, . . . , n−1);

(a_(#3,1,1)%3, a_(#3,1,2)%3, a_(#3,1,3)%3), (a_(#3,2,1)%3, a_(#3,2,2)%3,a_(#3,2,3)%3), . . . , (a_(#3,p,1)%3, a_(#3,p,2)%3, a_(#3,p,3)%3), . . ., (a_(#3,n−1,1)%3, a_(#3,n−1,2)%3, a_(#3,n−1,3)%3) and (b_(#3,1)%3,b_(#3,2)%3, b_(#3,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2),(1, 2, 0), (2, 0, 1), or (2, 1, 0) (where p=1, 2, 3, . . . , n−1);

-   -   

(a_(#k,1,1)%3, a_(#k,1,2)%3, a_(#k,1,3)%3), (a_(#k,2,1)%3, a_(#k,2,2)%3,a_(#k,2,3)%3), . . . , (a_(#k,p,1)%3, a_(#k,p,2)%3, a_(#k,p,3)%3), . . ., (a_(#k,n−1,1)%3, a_(#k,n−1,2)%3, a_(#k,n−1,3)%3) and (b_(#k,1)%3,b_(#k,2)%3, b_(#k,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2),(1, 2, 0), (2, 0, 1), or (2, 1, 0) (where p=1, 2, 3, . . . , n−1) (wherek=1, 2, 3, . . . , 3g);

-   -   

(a_(#3g−2,1,1)%3, a_(3g−2,1,2)%3, a_(3g−2,1,3)%3), (a_(3g−2,2,1)%3,a_(3g−2,2, 2)%3, a_(3g−2,2,3)%3), . . . , (a_(3g−2,p,1)%3,a_(3g−2,p,2)%3, a_(3g−2,p,3)%3), . . . , (a_(3g−2,n−1,1)%3,a_(3g−2,n−1,2)%3, a_(3g−2,n−1,3)%3) and (b_(3g−2,1)%3, b_(3g−2,2)%3,b_(3g−2,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0),(2, 0, 1), or (2, 1, 0) (where p=1, 2, 3, . . . , n−1);

(a_(#3g−1,1,1)%3, a_(#3g−1,1,2)%3, a_(#3g−1,1,3)%3), (a_(#3g−1,2,1)%3,a_(#3g−1,2,2)%3, a_(#3g−1,2,3)%3), . . . , (a_(#3g−1,p,1)%3,a_(#3g−1,p,2)%3, a_(#3g−1,p,3)%3), . . . , (a_(#3g−1,n−1,1)%3,a_(#3g−1,n−1,2)%3, a_(#3g−1,n−1,3)%3) and (b_(3g−1,1)%3, b_(3g−1,2)%3,b_(3g−1,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0),(2, 0, 1), or (2, 1, 0) (where p=1, 2, 3, . . . , n−1); and

(a_(#3g,1,1)%3, a_(#3g,1,2)%3, a_(#3g,1,3)%3), (a_(#3g,2,1)%3,a_(#3g,2,2)%3, a_(#3g,2,3)%3), . . . , (a_(#3g,p,1)%3, a_(#3g,p,2)%3,a_(#3g,p,3)%3), . . . , (a_(#3g,n−1,1)%3, a_(#3g,n−1,2)%3,a_(#3g,n−1,3)%3) and (b_(3g−1,1)%3, b_(3g−1,2)%3, b_(3g−1,3,3)%3) areany of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1,0) (where p=1, 2, 3, . . . , n−1).

Taking ease of performing encoding into account, it is desirable for one“0” to be present among the three items (b_(#k,1)%3, b_(#k,2)%3,b_(#k,3)%3) (where k=1, 2, . . . , 3g) in equations 9-1 to 9-3g. This isbecause of a feature that, if D⁰=1 holds true and b_(#k,1), b_(#k,2) andb_(#k,3) are integers equal to or greater than 0 at this time, paritypart P can be found sequentially.

Also, in order to provide relevancy between parity bits and data bits ofthe same point in time, and to facilitate a search for a code havinghigh correction capability, it is desirable for:

-   -   one “0” to be present among the three items (a_(#k,1,1)%3,        a_(#k,1,2)%3, a_(#k,1,3)%3);

    -   one “0” to be present among the three items (a_(#k,2,1)%3,        a_(#k,2,2)%3, a_(#k,2,3)%3);

    -   

one “0” to be present among the three items (a_(#k,p,1)%3, a_(#k,p,2)%3,a_(#k,p,3)%3);

-   -   

one “0” to be present among the three items (a_(#k,n-−1,1)%3,a#_(k, n−1,2)%3, a_(#k, n−1,3)%3), (where k=1, 2, . . . , 3g).

Next, an LDPC-CC of a time varying period of 3g (where g=2, 3, 4, 5, . .. ) that takes case of encoding into account is considered. At thistime, if the coding rate is (n−1)/n (where n is an integer equal to orgreater than 2), LDPC-CC parity check polynomials can be represented asshown below.

$\begin{matrix}{\mspace{79mu}\lbrack 11\rbrack} & \; \\{{{\left( {D^{{a{\# 1}},1,1} + D^{{a{\# 1}},1,2} + D^{{a{\# 1}},1,3}} \right){X_{1}(D)}} + {\left( {D^{{a{\# 1}},2,1} + D^{{a{\# 1}},2,2} + D^{{a{\# 1}},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 1}},{n - 1},1} + D^{{a{\# 1}},{n - 1},2} + D^{{a{\# 1}},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 1}},1} + D^{{b{\# 1}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 11\text{-}1} \right) \\{{{\left( {D^{{a{\# 2}},1,1} + D^{{a{\# 2}},1,2} + D^{{a{\# 2}},1,3}} \right){X_{1}(D)}} + {\left( {D^{{a{\# 2}},2,1} + D^{{a{\# 2}},2,2} + D^{{a{\# 2}},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 2}},{n - 1},1} + D^{{a{\# 2}},{n - 1},2} + D^{{a{\# 2}},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 2}},1} + D^{{b{\# 2}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 11\text{-}2} \right) \\{{{\left( {D^{{a{\# 3}},1,1} + D^{{a{\# 3}},1,2} + D^{{a{\# 3}},1,3}} \right){X_{1}(D)}} + {\left( {D^{{a{\# 3}},2,1} + D^{{a{\# 3}},2,2} + D^{{a{\# 3}},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 3}},{n - 1},1} + D^{{a{\# 3}},{n - 1},2} + D^{{a{\# 3}},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 3}},1} + D^{{b{\# 3}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 11\text{-}3} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{a\# k},1,1} + D^{{a\# k},1,2} + D^{{a\# k},1,3}} \right){X_{1}(D)}} + {\left( {D^{{a\# k},2,1} + D^{{a\# k},2,2} + D^{{a\# k},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a\# k},{n - 1},1} + D^{{a\# k},{n - 1},2} + D^{{a\# k},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{b\# k},1} + D^{{b\# k},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 11\text{-}k} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{{a{\# 3}g} - 2},1,1} + D^{{{a{\# 3}g} - 2},1,2} + D^{{{a{\# 3}g} - 2},1,3}} \right){X_{1}(D)}} + {\left( {D^{{{a{\# 3}g} - 2},2,1} + D^{{{a{\# 3}g} - 2},2,2} + D^{{{a{\# 3}g} - 2},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{{a{\# 3}g} - 2},{n - 1},1} + D^{{{a{\# 3}g} - 2},{n - 1},2} + D^{{{a{\# 3}g} - 2},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{{b{\# 3}g} - 2},1} + D^{{{b{\# 3}g} - 2},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 11\text{-}\left( {3g\text{-}2} \right)} \right) \\{{{\left( {D^{{{a{\# 3}g} - 1},1,1} + D^{{{a{\# 3}g} - 1},1,2} + D^{{{a{\# 3}g} - 1},1,3}} \right){X_{1}(D)}} + {\left( {D^{{{a{\# 3}g} - 1},2,1} + D^{{{a{\# 3}g} - 1},2,2} + D^{{{a{\# 3}g} - 1},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{{a{\# 3}g} - 1},{n - 1},1} + D^{{{a{\# 3}g} - 1},{n - 1},2} + D^{{{a{\# 3}g} - 1},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{{b{\# 3}g} - 1},1} + D^{{{b{\# 3}g} - 1},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 11\text{-}\left( {3g\text{-}1} \right)} \right) \\{{{\left( {D^{{a{\# 3}g},1,1} + D^{{a{\# 3}g},1,2} + D^{{a{\# 3}g},1,3}} \right){X_{1}(D)}} + {\left( {D^{{a{\# 3}g},2,1} + D^{{a{\# 3}g},2,2} + D^{{a{\# 3}g},2,3}} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 3}g},{n - 1},1} + D^{{a{\# 3}g},{n - 1},2} + D^{{a{\# 3}g},{n - 1},3}} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 3}g},1} + D^{{b{\# 3}g},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 11\text{-}3g} \right)\end{matrix}$

At this time, X₁(D), X₂(D), . . . , X_(n−1)(D) are polynomialrepresentations of data (information) X₁, X₂, . . . , X_(n−1), and P(D)is a parity polynomial representation. Here, in equations 11-1 to 11-3g,parity check polynomials are assumed such that there are three terms inX₁, X₂, . . . , X_(n−1)(D), and P(D) respectively. In an LDPC-CC of atime varying period of 3g and a coding rate of (n−1)/n (where n is aninteger equal to or greater than 2), the parity part and information attime i are represented by Pi and X_(i,1), X_(i,2), . . . , X_(i,n−1)respectively. If i %3g=k (where k=0, 1, 2, . . . , 3g−1) is assumed atthis time, a parity check polynomial of equation 11−(k+1) holds true.For example, if i=2, i %3=2 (k=2), and therefore equation 12 holds true.[12](D ^(a#3,1,1) +D ^(a#3,1,2) +D ^(a#3,1,3))X _(2,1)+(D ^(a#3,2,1) +D^(a#3,2,2) +D ^(a#3,2,3))X _(2,2)+ . . . +(D ^(a#3,n-1,1) +D^(a#3,n-1,2) +D ^(a#3,n-1,3))X _(2,n−1)+(D ^(b#3,1) +D ^(b#3,2))P₂=0  (Equation 12)

If <Condition #3> and <Condition #4> are satisfied at this time, thepossibility of being able to create a code having higher errorcorrection capability is increased.

<Condition #3>

In equations 11-1 to 11-3g, combinations of degrees of X₁(D), X₂(D), . .. , X_(n−1)(D). and P(D) satisfy the following condition:

(a_(#1,1,1)%3, a_(#1,1,2)%3, a_(#1,1,3)%3), (a_(#1,2,1)%3, a_(#1,2,2)%3,a_(#1,2,3)%3), . . . , (a_(#1,p,1)%3, a_(#1,p,2)%3, a_(#1,p,3)%3), . . ., and (a_(#1,n−1,1)%3, a_(#1,n−1,2)%3, a_(#1,n−1,3)%3) are any of (0, 1,2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0) (where p=1,2, 3, . . . , n−1);

(a_(#2,1,1)%3, a_(#2,1,2)%3, a_(#2,1,3)%3), (a_(#2,2,1)%3, a_(#2,2,2)%3,a_(#2,2,3)%3), . . . , (a_(#2,p,1)%3, a_(#2,p,2)%3, a_(#2,p,3)%3), . . ., and (a_(#2,n−1,1)%3, a_(#2,n−1,2)%3, a_(#2,n−1,3)%3) are any of (0, 1,2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0) (where p=1,2, 3, . . . , n−1);

(a_(#3,1,1)%3, a_(#3,1,2)%3, a_(#3,1,3)%3), (a_(#3,2,1)%3, a_(#3,2,2)%3,a_(#3,2,3)%3), . . . , (a_(#3,p,1)%3, a_(#3,p,2)%3, a_(#3,p,3)%3), . . ., and (a_(#3,n−1,1)%3, a_(#3,n−1,2)%3, a_(#3,n−1,3)%3) are any of (0, 1,2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0) (where p=1,2, 3, . . . , n−1);

-   -   

(a_(#k,1,1)%3, a_(#k,1,2)%3, a_(#k,1,3)%3), (a_(#k,2,1)%3, a_(#k,2,2)%3,a_(#k,2,3)%3), . . . , (a_(#k,p,1)%3, a_(#k,p,2)%3, a_(#k,p,3)%3), . . ., and (a_(#k,n−1,1)%3, a_(#k,n−1,2)%3, a_(#k,n−1,3)%3) are any of (0, 1,2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0) (where p=1,2, 3, . . . , n−1, and k=1, 2, 3, . . . , 3g);

-   -   

(a_(#3g−2,1,1)%3, a_(#3g−2,1,2)%3, a_(#3g−2,1,3)%3), (a_(#3g−2,2,1)%3,a_(#3g−2,2, 2)%3, a_(#3g−2,2,3)%3), . . . , (a_(#3g−2,p,1)%3,a_(#3g−2,p,2)%3, a_(#3g−2,p,3)%3), . . . , and (a_(#3g−2,n−1,1)%3,a_(#3g−2,n−1,2)%3, a_(#3g−2,n−1,3)%3) are any of (0, 1, 2), (0, 2, 1),(1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0) (where p=1, 2, 3, . . . ,n−1);

(a_(#3g−1,1,1)%3, a_(#3g−1,1,2)%3, a_(#3g−1,1,3)%3), (a_(#3g−1,2,1)%3,a_(#3g−1,2,2)%3, a_(#3g−1,2,3)%3), . . . , (a_(#3g−1,p,1)%3,a_(#3g−1,p,2)%3, a_(#3g−1,p,3)%3), . . . , and (a_(#3g−1,n−1,1)%3,a_(#3g−1,n−1,2)%3, a_(#3g−1,n−1,3)%3) are any of (0, 1, 2), (0, 2, 1),(1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0) (where p=1, 2, 3, . . . ,n−1); and

(a_(#3g,1,1)%3, a_(#3g,1,2)%3, a_(#3g,1,3)%3), (a_(#3g,2,1)%3,a_(#3g,2,2)%3, a_(#3g,2,3)%3), . . . , (a_(#3g,p,1)%3, a_(#3g,p,2)%3,a_(#3g,p,3)%3), . . . , and (a_(#3g,n−1,1)%3, a_(#3g,n−1,2)%3,a_(#3g,n−1,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0),(2, 0, 1), or (2, 1, 0) (where p=1, 2, 3, . . . , n−1). In addition, inequations 11-1 to 11-3g, combinations of degrees of P(D) satisfy thefollowing condition:

(b_(#1,1)%3, b_(#1,2)%3), (b_(#2,1)%3, b_(#2,2)%3), (b_(#3,1)%3,b_(#3,2)%3), . . . , (b_(#k,1)%3, b_(#k,2)%3), . . . , (b_(#3g−2,1)%3,b_(#3g−2,2)%3), (b_(#3g−1,2)%3, b_(#3g−1,2)%3), and (b_(#3g,1)%3,b_(#3g,2)%3) are any of (1, 2), or (2, 1) (where k=1, 2, 3, . . . , 3g).

<Condition #3> has a similar relationship with respect to equations 11-1to 11-3g as <Condition #2> has with respect to equations 9-1 to 9-3g. Ifthe condition below (<Condition #4>) is added for equations 11-1 to11-3g in addition to <Condition #3>, the possibility of being able tocreate an LDPC-CC having higher error correction capability isincreased.

<Condition #4>

Degrees of P(D) of equations 11-1 to 11-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the values of 6g degrees of (b_(#1,1)%3g, b_(#1,2)%3g),(b_(#2,1)%3g, b_(#2,2)%3g), (b_(#3,1)%3g, b_(#3,2)%3g), . . . ,(b_(#k,1)%3g, b_(#k,2)%3g), . . . , (b_(#3g−2,1)%3g, b_(#3g−2,2)%3g),(b_(#3−1,1)%3g, b_(#3g−1,2)%3g), (b_(#3g,1)%3g, b_(#3g,2)%3g).

The possibility of obtaining good error correction capability is high ifthere is also randomness while regularity is maintained for positions atwhich 1's are present in a parity check matrix. With an LDPC-CC forwhich the time varying period is 3g (where g=2, 3, 4, 5, . . . ) and thecoding rate is (n−1)/n (where n is an integer equal to or greater than2) that has parity check polynomials of equations 11-1 to 11-3g, if acode is created in which <Condition #4> is applied in addition to<Condition #3>, it is possible to provide randomness while maintainingregularity for positions at which 1's are present in a parity checkmatrix, and therefore the possibility of obtaining good error correctioncapability is increased.

Next, an LDPC-CC of a time varying period of 3g (where g=2, 3, 4, 5, . .. ) is considered that enables encoding to be performed easily andprovides relevancy to parity bits and data bits of the same point intime. At this time, if the coding rate is (n−1)/n (where n is an integerequal to or greater than 2), LDPC-CC parity check polynomials can berepresented as shown below.

$\begin{matrix}{\mspace{79mu}\lbrack 13\rbrack} & \; \\{{{\left( {D^{{a{\# 1}},1,1} + D^{{a{\# 1}},1,2} + 1} \right){X_{1}(D)}} + {\left( {D^{{a{\# 1}},2,1} + D^{{a{\# 1}},2,2} + 1} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 1}},{n - 1},1} + D^{{a{\# 1}},{n - 1},2} + 1} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 1}},1} + D^{{b{\# 1}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 13\text{-}1} \right) \\{{{\left( {D^{{a{\# 2}},1,1} + D^{{a{\# 2}},1,2} + 1} \right){X_{1}(D)}} + {\left( {D^{{a{\# 2}},2,1} + D^{{a{\# 2}},2,2} + 1} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 2}},{n - 1},1} + D^{{a{\# 2}},{n - 1},2} + 1} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 2}},1} + D^{{b{\# 2}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 13\text{-}2} \right) \\{{{\left( {D^{{a{\# 3}},1,1} + D^{{a{\# 3}},1,2} + 1} \right){X_{1}(D)}} + {\left( {D^{{a{\# 3}},2,1} + D^{{a{\# 3}},2,2} + 1} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 3}},{n - 1},1} + D^{{a{\# 3}},{n - 1},2} + 1} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 3}},1} + D^{{b{\# 3}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 13\text{-}3} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{a\# k},1,1} + D^{{a\# k},1,2} + 1} \right){X_{1}(D)}} + {\left( {D^{{a\# k},2,1} + D^{{a\# k},2,2} + 1} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a\# k},{n - 1},1} + D^{{a\# k},{n - 1},2} + 1} \right){X_{n - 1}(D)}} + {\left( {D^{{b\# k},1} + D^{{b\# k},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 13\text{-}k} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{{a{\# 3}g} - 2},1,1} + D^{{{a{\# 3}g} - 2},1,2} + 1} \right){X_{1}(D)}} + {\left( {D^{{{a{\# 3}g} - 2},2,1} + D^{{{a{\# 3}g} - 2},2,2} + 1} \right){X_{2}(D)}} + \ldots + {\left( {D^{{{a{\# 3}g} - 2},{n - 1},1} + D^{{{a{\# 3}g} - 2},{n - 1},2} + 1} \right){X_{n - 1}(D)}} + {\left( {D^{{{b{\# 3}g} - 2},1} + D^{{{b{\# 3}g} - 2},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 13\text{-}\left( {3g\text{-}2} \right)} \right) \\{{{\left( {D^{{{a{\# 3}g} - 1},1,1} + D^{{{a{\# 3}g} - 1},1,2} + 1} \right){X_{1}(D)}} + {\left( {D^{{{a{\# 3}g} - 1},2,1} + D^{{{a{\# 3}g} - 1},2,2} + 1} \right){X_{2}(D)}} + \ldots + {\left( {D^{{{a{\# 3}g} - 1},{n - 1},1} + D^{{{a{\# 3}g} - 1},{n - 1},2} + 1} \right){X_{n - 1}(D)}} + {\left( {D^{{{b{\# 3}g} - 1},1} + D^{{{b{\# 3}g} - 1},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 13\text{-}\left( {3g\text{-}1} \right)} \right) \\{{{\left( {D^{{a{\# 3}g},1,1} + D^{{a{\# 3}g},1,2} + 1} \right){X_{1}(D)}} + {\left( {D^{{a{\# 3}g},2,1} + D^{{a{\# 3}g},2,2} + 1} \right){X_{2}(D)}} + \ldots + {\left( {D^{{a{\# 3}g},{n - 1},1} + D^{{a{\# 3}g},{n - 1},2} + 1} \right){X_{n - 1}(D)}} + {\left( {D^{{b{\# 3}g},1} + D^{{b{\# 3}g},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 13\text{-}3g} \right)\end{matrix}$

At this time, X₁(D), X₂(D), . . . , X_(n−1)(D) are polynomialrepresentations of data (information) X₁, X₂, . . . , X_(n−1), and P(D)is a parity polynomial representation. In equations 13-1 to 13-3g,parity check polynomials are assumed such that there are three terms inX₁(D), X₂(D), . . . , X_(n−1)(D), and P(D) respectively, and term D⁰ ispresent in X₁(D), X₂(D), . . . , X_(n−1)(D), and P(D) (where k=1, 2, 3,. . . , 3g).

In an LDPC-CC of a time varying period of 3g and a coding rate of(n−1)/n (where n is an integer equal to or greater than 2), the paritypart and information at time i are represented by Pi and X_(1,1),X_(1,2), . . . , X_(i,n−1) respectively. If i %3g=k (where k=0, 1, 2, .. . , 3g−1) is assumed at this time, a parity check polynomial ofequation 13-(k+1) holds true. For example, if i=2, i %3g=2 (k=2), andtherefore equation 14 holds true.[14](D ^(a#3,1,1) +D ^(a#3,1,2)+1)X _(2,1)+(D ^(a#3,2,1) +D ^(a#3,2,2)+1)X_(2,2)+ . . . +(D ^(a#3,n-1,1) +D ^(a#3,n-1,2)+1)X _(2,n−1)+(D ^(b#3,1)+D ^(b#3,2)+1)P ₂=0  (Equation 14)

If following <Condition #5> and <Condition #6> are satisfied at thistime, the possibility of being able to create a code having higher errorcorrection capability is increased.

<Condition #5>

In equations 13-1 to 13-3g, combinations of degrees of X₁(D), X₂(D), . .. , X_(n−1)(D), and P(D) satisfy the following condition:

(a_(#1,1,1)%3, a_(#1,1,2)%3), (a_(#1,2,1)%3, a_(#1,2,2)%3), . . . ,(a_(#1,p,1)%3, a_(#1,p,2)%3), . . . , and (a_(#1,n−1,1)%3,a_(#1,n−1,2)%3) are any of (1, 2), (2, 1) (p=1, 2, 3, . . . , n−1);

(a_(#2,1,1)%3, a_(#2,1,2)%3), (a_(#2,2,1)%3, a_(#2,2,2)%3), . . . ,(a_(#2,p,1)%3, a_(#2,p,2)%3), . . . , and (a_(#2,n−1,1)%3,a_(#2,n−1,2)%3) are any of (1, 2), or (2, 1) (where p=1, 2, 3, . . . ,n−1);

(a_(#3,1,1)%3, a_(#3,1,2)%3), (a_(#3,2,1)%3, a_(#3,2,2)%3), . . . ,(a_(#3,p,1)%3, a_(#3,p,2)%3), . . . , and (a_(#3,n−1,1)%3,a_(#3,n−1,2)%3) are any of (1, 2), or (2, 1) (where p=1, 2, 3, . . . ,n−1);

-   -   

(a_(#k,1,1)%3, a_(#k,1,2)%3), (a_(#k,2,1)%3, a_(#k,2,2)%3), . . . ,(a_(#k,p,1)%3, a_(#k,p,2)%3), . . . , and (a_(#k,n−1,1)%3,a_(#k,n−1,2)%3) are any of (1, 2) or (2, 1) (where p=1, 2, 3, . . . ,n−1) (where k=1, 2, 3, . . . , 3g)

(a_(#3g−2,1,1)%3, a_(#3g−2,1,2)%3), (a_(#3g−2,2,1)%3, a_(#3g−2,2,2)%3),. . . , (a_(#3g−2,p,1)%3, a_(#3g−2,p,2)%3), . . . , and(a_(#3g−2,n−1,1)%3, a_(#3g−2,n−1,2)%3) are any of (1, 2), or (2, 1)(where p=1, 2, 3, . . . , n−1);

(a_(#3g−1,1,1)%3, a_(#3g−1,1,2)%3), (a_(#3g−1,2,1)%3, a_(#3g−1,2,2)%3),. . . , (a_(#3g−1,p,1)%3, a_(#3g−1,p,2)%3), . . . , and(a_(#3g−1,n−1,1)%3, a_(#3g−1,n−1,2)%3) are any of (1, 2), or (2, 1)(where p=1, 2, 3, . . . , n−1); and

(a_(#3g,1,1)%3, a_(#3g,1,2)%3), (a_(#3g,2,1)%3, a_(#3g,2,2)%3), . . . ,(a_(#3g,p,1)%3, a_(#3g,p,2)%3), . . . , and (a_(#3g,n−1,1)%3,a_(#3g,n−1,2)%3) are any of (1, 2), (2, 1) (where p=1, 2, 3, . . . ,n−1). In addition, in equations 13-1 to 13-3g, combinations of degreesof P(D) satisfy the following condition:

(b_(#1,1)%3, b_(#1,2)%3), (b_(#2,1)%3, b_(#2,2)%3), (b_(#3,1)%3,b_(#3,2)%3), . . . , (b_(#k,1)%3, b_(#k,2)%3), . . . , (b_(#3g−2,1)%3,b_(#3g−2,2)%3), (b_(#3g−1,1)%3, b_(#3g−1,2)%3), and (b_(#3g,1)%3,b_(#3g,2)%3) are any of (1, 2), or (2, 1) (where k=1, 2, 3, . . . , 3g).

<Condition #5> has a similar relationship with respect to equations 13-1to 13-3g as <Condition #2> has with respect to equations 9-1 to 9-3g. Ifthe condition below (<Condition #6>) is added for equations 13-1 to13-3g in addition to <Condition #5>. the possibility of being able tocreate a code having high error correction capability is increased.

<Condition #6>

Degrees of X1(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1, 1, 1)%3g,a_(#1,1,2)%3g), (a_(#2,1,1)%3g, a_(#2,1,2)%3g), . . . , (a_(#p,1,1)%3g,a_(#p,1,2)%3g), . . . , and (a_(#3g,1,1)%3g, a_(#3g,1,2)%3g) (where p=1,2, 3, . . . , 3g);

Degrees of X2(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1,2,1)%3g,a_(#1,2,2)%3g), (a_(#2,2,1)%3g, a_(#2, 2, 2)%3g), . . . ,(a_(#p,2,1)%3g, a_(#p,2,2)%3g), . . . , and (a_(#3,2,1)%3g,a_(#3,2,2)%3g) (where p=1, 2, 3, . . . , 3g);

Degrees of X3(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1,3,1)%3g,a_(#1,3,2)%3g), (a_(#2,3,1)%3g, a_(#2,3,2)%3g), . . . , (a_(#p,3,1)%3g,a_(#p,3,2)%3g), . . . , and (a_(#3,3,1)%3g, a_(#g,3,2)%3g) (where p=1,2, 3, . . . , 3g);

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Degrees of Xk(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1,k,1)%3g,a_(#1,k,2)%3g), (a_(#2,k,1)%3g, a_(#2,k,2)%3g), . . . , (a_(#p,k,1)%3g,a_(#p,k,2)%3g), . . . , and (a_(#3g,k)1%3g, a_(#3g,k),2%3g) (where p=1,2, 3, . . . , 3g, and k=1, 2, 3, . . . , n−1);

-   -   

Degrees of X_(n−1)(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1,n−1,1)%3g,a_(#1,n−1,2)%3g), (a_(#2,n−1,1)%3g, a_(#2,n−1,2)%3g), . . . ,(a_(#p,n−1,1)%3g, a_(#p,n−1,2)%3g), . . . , and (a_(#3g,n−1,1)%3g,a_(#3g,n−1,2)%3g) (where p=1, 2, 3, . . . , 3g); and

Degrees of P(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (b_(#1,1)%3g, b_(#1,2)%3g),(b_(#2,1)%3g, b_(#2,2)%3g), (b_(#3,1)%3g, b_(#3,2)%3g), . . . ,(b_(#k,1)%3g, b_(#k,2)%3g), . . . , (b_(#3g−2,1)%3g, b_(#3g−2,2)%3g),(b_(#3g−1,1)%3g, b_(#3g−1,2)%3g) and (b_(#3g,1)%3g, b_(#3g,2)%3g) (wherek=1, 2, 3, . . . , n−1).

The possibility of obtaining good error correction capability is high ifthere is also randomness while regularity is maintained for positions atwhich 1's are present in a parity check matrix. With an LDPC-CC forwhich the time varying period is 3g (where g=2, 3, 4, 5, . . . ) and thecoding rate is (n−1)/n (where n is an integer equal to or greater than2) that has parity check polynomials of equations 13-1 to 13-3g, if acode is created in which <Condition #6> is applied in addition to<Condition #5>, it is possible to provide randomness while maintainingregularity for positions at which 1's are present in a parity checkmatrix, and therefore the possibility of obtaining good error correctioncapability is increased.

The possibility of being able to create an LDPC-CC having higher errorcorrection capability is also increased if a code is created using<Condition #6′> instead of <Condition #6>, that is, using <Condition#6′> in addition to <Condition #5>.

<Condition #6′>

Degrees of X₁(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1,1,1)%3g,a_(#1,1,2)%3g), (a_(#2,1,1)%3g, a_(#2,1,2)%3g), . . . , (a_(#p,1,1)%3g,a_(#p,1,2)%3g), . . . , and (a_(#3g,1),1%3g, a_(#3g,1,2)%3g) (where p=1,2, 3, . . . , 3g);

Degrees of X2(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1,2,1)%3g,a_(#1,2,2)%3g), (a_(#2,2,1)%3g, a_(#2, 2, 2)%3g), . . . ,(a_(#p,2,1)%3g, a_(#p,2,2)%3g), . . . , and (a_(#3,2,1)%3g,a_(#3g,2,2)%3g) (where p=1, 2, 3, . . . , 3g);

Degrees of X3(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1,3,1)%3g,a_(#1,3,2)%3g), (a_(#2,3,1)%3g, a_(#2,3,2)%3g), . . . , (a_(#p,3,1)%3g,a_(#p,3,2)%3g), . . . , and (a_(#3g,3,1)%3g, a_(#3g,3,2)%3g) (where p=1,2, 3, . . . , 3g);

-   -   

Degrees of Xk(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1,k,1)%3g,a_(#1,k,2)%3g), (a_(#2,k,1)%3g, a_(#2,k,2)%3g), . . . , (a_(#p,k,1)%3g,a_(#p,k,2)%3g), . . . , (a_(#3g,k,1)%3g, a_(#3q,k,2)%3g) (where p=1, 2,3, . . . , 3g, and k=1, 2, 3, . . . , n−1);

-   -   

Degrees of X_(n−1)(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1,n−1,1)%3g,a_(#1,n−1,2)%3g), (a_(#2,n−1,1)%3g, a_(#2,n−1,2)%3g), . . . ,(a_(#p,n−1,1)%3g, a_(#p,n−1,2)%3g), . . . , (a_(#3g,n−1,1)%3g,a_(#3g,n−1,2)%3g) (where p=1, 2, 3, . . . , 3g); or

Degrees of P(D) of equations 13-1 to 13-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (b_(#1,1)%3g, b_(#1,2)%3g),(b_(#2,1)%3g, b_(#2,2)%3g), (b_(#3,1)%3g, b_(#3,2)%3g), . . . ,(b_(#k,1)%3g, b_(#k,2)%3g), . . . , (b_(#3g,−2,1)%3g, b_(#g−2,23)%3g),(b_(#3g−1,1)%3g, b_(#3g−1,2)%3g), (b_(#3g,1)%3g, b_(#3g,2)%3g) (wherek=1, 2, 3, . . . , 3g).

The above description relates to an LDPC-CC of a time varying period of3g and a coding rate of (n−1)/n (where n is an integer equal to orgreater than 2). Below, conditions are described for degrees of anLDPC-CC of a time varying period of 3g and a coding rate of 1/2 (n=2).

Consider equations 15-1 to 15-3g as parity check polynomials of anLDPC-CC for which the time varying period is 3g (where g=1, 2, 3, 4, . .. ) and the coding rate is 1/2 (n=2).

$\begin{matrix}{\mspace{79mu}\lbrack 15\rbrack} & \; \\{{{\left( {D^{{a{\# 1}},1,1} + D^{{a{\# 1}},1,2} + D^{{a{\# 1}},1,3}} \right){X(D)}} + {\left( {D^{{b{\# 1}},1} + D^{{b{\# 1}},2} + D^{{b{\# 1}},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 15\text{-}1} \right) \\{{{\left( {D^{{a{\# 2}},1,1} + D^{{a{\# 2}},1,2} + D^{{a{\# 2}},1,3}} \right){X(D)}} + {\left( {D^{{b{\# 2}},1} + D^{{b{\# 2}},2} + D^{{b{\# 2}},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 15\text{-}2} \right) \\{{{\left( {D^{{a{\# 3}},1,1} + D^{{a{\# 3}},1,2} + D^{{a{\# 3}},1,3}} \right){X(D)}} + {\left( {D^{{b{\# 3}},1} + D^{{b{\# 3}},2} + D^{{b{\# 3}},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 15\text{-}3} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{a\# k},1,1} + D^{{a\# k},1,2} + D^{{a\# k},1,3}} \right){X(D)}} + {\left( {D^{{b\# k},1} + D^{{b\# k},2} + D^{{b\# k},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 15\text{-}k} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{{a{\# 3}g} - 2},1,1} + D^{{{a{\# 3}g} - 2},1,2} + D^{{{a{\# 3}g} - 2},1,3}} \right){X(D)}} + {\left( {D^{{{b{\# 3}g} - 2},1} + D^{{{b{\# 3}g} - 2},2} + D^{{{b{\# 3}g} - 2},3}} \right){P(D)}}} = 0} & {\left( {{Equation}\mspace{14mu} 15\text{-}\left( {3g\text{-}2} \right)} \right)\mspace{14mu}} \\{{{\left( {D^{{{a{\# 3}g} - 1},1,1} + D^{{{a{\# 3}g} - 1},1,2} + D^{{{a{\# 3}g} - 1},1,3}} \right){X(D)}} + {\left( {D^{{{b{\# 3}g} - 1},1} + D^{{{b{\# 3}g} - 1},2} + D^{{{b{\# 3}g} - 1},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 15\text{-}\left( {3g\text{-}1} \right)} \right) \\{{{\left( {D^{{a{\# 3}g},1,1} + D^{{a{\# 3}g},1,2} + D^{{a{\# 3}g},1,3}} \right){X(D)}} + {\left( {D^{{b{\# 3}g},1} + D^{{b{\# 3}g},2} + D^{{b{\# 3}g},3}} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 15\text{-}3g} \right)\end{matrix}$

At this time, X is a polynomial representation of data (information) Xand P(D) is a parity polynomial representation. Here, in equations 15-1to 15-3g, parity check polynomials are assumed such that there are threeterms in X(D) and P(D) respectively.

Thinking in the same way as in the case of an LDPC-CC of a time varyingperiod of 3 and an LDPC-CC of a time varying period of 6, thepossibility of being able to obtain higher error correction capabilityis increased if the condition below (<Condition #2-1>) is satisfied inan LDPC-CC of a time varying period of 3g and a coding rate of 1/2 (n=2)represented by parity check polynomials of equations 15-1 to 15-3g.

In an LDPC-CC of a time varying period of 3g and a coding rate of 1/2(n=2), the parity part and information at time i are represented by Piand X_(i,1) respectively. If i %3g=k (where k=0, 1, 2, . . . , 3g−1) isassumed at this time, a parity check polynomial of equation 15-(k+1)holds true. For example, if i=2, i %3g=2 (k=2), and therefore equation16 holds true.[16](D ^(a#3,1,1) +D ^(a#3,1,2) +D ^(a#3,1,3))X _(2,1)+(D ^(b#3,1) +D^(b#3,2) +D ^(a#3,3))P ₂=0  (Equation 16)

In equations 15-1 to 15-3g, it is assumed that a_(#k,1,1), a_(#1,1,2),and a_(#k,1,3) are integers (where a_(#k,1,1)≠a_(#k,1,2)≠a_(#k,1,3))(where k=1, 2, 3, . . . , 3g). Also, it is assumed that b_(#k,1),b_(#k,2), and b_(#k,3) are integers (where b_(#k,1)≠b_(#k,2)≠b_(#k,3)).A parity check polynomial of equation 15-k (k=1, 2, 3, . . . , 3g) iscalled “check equation #k.” A sub-matrix based on the parity checkpolynomial of equation 15-k is designated k-th sub-matrix H_(k). Next,an LDPC-CC of a time varying period of 3g is considered that isgenerated from first sub-matrix H₁, second sub-matrix H₂, thirdsub-matrix H₃, . . . , and 3g-th sub-matrix H₃ s

<Condition #2-1>

In equations 15-1 to 15-3g, combinations of degrees of X(D) and P(D)satisfy the following condition:

(a_(#1,1,1)%3, a_(#1,1,2)%3, a_(#1,1,3)%3) and (b_(#1,1)%3, b_(#1,2)%3,b_(#1,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2,0, 1), or (2, 1, 0);

(a_(#2,1,1)%3, a_(#2,1,2)%3, a_(#2,1,3)%3) and (b_(#2,1)%3, b_(#2,2)%3,b_(#2,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2,0, 1), or (2, 1, 0);

(a_(#3,1,1)%3, a_(#3,1,2)%3, a_(#3,1,3)%3) and (b_(#3,1)%3, b_(#3,2)%3,b_(#3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2,0, 1), or (2, 1, 0);

-   -   

(a_(#k,1,1)%3, a_(#k,1,2)%3, a_(#k,1,3)%3) and (b_(#k,1)%3, b_(#k,2)%3,b_(#k,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2,0, 1), or (2, 1, 0) (where k=1, 2, 3, . . . , 3g);

-   -   

(a_(#3g−2,1,1)%3, a_(#3g−2,1,2)%3, a_(#3g−2,1,3)%3) and (b_(#3g−2,1)%3,b_(#3g−2,2)%3, b_(#3g−2,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0,2), (1, 2, 0), (2, 0, 1), or (2, 1, 0);

(a_(#3g−1,1,1)%3, a_(#3g−1,1,2)%3, a_(#3g−1,1,3)%3) and (b_(#3g−1,1)%3,b_(#3g−1,2)%3, b_(#3g−1,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0,2), (1, 2, 0), (2, 0, 1), or (2, 1, 0); and

(a_(#3g,1,1)%3, a_(#3g,1,2)%3, a_(#3g,1,3)%3) and (b_(#3g,1)%3,b_(#3g,2)%3, b_(#3g,3,3)%3) are any of (0, 1, 2), (0, 2, 1), (1, 0, 2),(1, 2, 0), (2, 0, 1), or (2, 1, 0);

Taking ease of performing encoding into account, it is desirable for one“0” to be present among the three items (b_(#k,1)%3, b_(#k,2)%3,b_(#k,3)%3) (where k=1, 2, . . . , 3g) in equations 15-1 to 15-3g. Thisis because of a feature that, if D⁰=1 holds true and b_(#k,1), b_(#k,2)and b_(#k,3) are integers equal to or greater than 0 at this time,parity part P can be found sequentially.

Also, in order to provide relevancy between parity bits and data bits ofthe same point in time, and to facilitate a search for a code havinghigh correction capability, it is desirable for one “0” to be presentamong the three items (a_(#k,1,1)%3, a_(#k,1,2)%3, a_(#k,1,3)%3) (wherek=1, 2, . . . , 3g).

Next, an LDPC-CC of a time varying period of 3g (where g=2, 3, 4, 5, . .. ) that takes ease of encoding into account is considered. At thistime, if the coding rate is 1/2 (n=2), LDPC-CC parity check polynomialscan be represented as shown below.

$\begin{matrix}{\mspace{79mu}\lbrack 17\rbrack} & \; \\{{{\left( {D^{{a{\# 1}},1,1} + D^{{a{\# 1}},1,2} + D^{{a{\# 1}},1,3}} \right){X(D)}} + {\left( {D^{{b{\# 1}},1} + D^{{b{\# 1}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 17\text{-}1} \right) \\{{{\left( {D^{{a{\# 2}},1,1} + D^{{a{\# 2}},1,2} + D^{{a{\# 2}},1,3}} \right){X(D)}} + {\left( {D^{{b{\# 2}},1} + D^{{b{\# 2}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 17\text{-}2} \right) \\{{{\left( {D^{{a{\# 3}},1,1} + D^{{a{\# 3}},1,2} + D^{{a{\# 3}},1,3}} \right){X(D)}} + {\left( {D^{{b{\# 3}},1} + D^{{b{\# 3}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 17\text{-}3} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{a\# k},1,1} + D^{{a\# k},1,2} + D^{{a\# k},1,3}} \right){X(D)}} + {\left( {D^{{b\# k},1} + D^{{b\# k},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 17\text{-}k} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{{a{\# 3}g} - 2},1,1} + D^{{{a{\# 3}g} - 2},1,2} + D^{{{a{\# 3}g} - 2},1,3}} \right){X(D)}} + {\left( {D^{{{b{\# 3}g} - 2},1} + D^{{{b{\# 3}g} - 2},2} + 1} \right){P(D)}}} = 0} & {\left( {{Equation}\mspace{14mu} 17\text{-}\left( {3g\text{-}2} \right)} \right)\mspace{14mu}} \\{{{\left( {D^{{{a{\# 3}g} - 1},1,1} + D^{{{a{\# 3}g} - 1},1,2} + D^{{{a{\# 3}g} - 1},1,3}} \right){X(D)}} + {\left( {D^{{{b{\# 3}g} - 1},1} + D^{{{b{\# 3}g} - 1},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 17\text{-}\left( {3g\text{-}1} \right)} \right) \\{{{\left( {D^{{a{\# 3}g},1,1} + D^{{a{\# 3}g},1,2} + D^{{a{\# 3}g},1,3}} \right){X(D)}} + {\left( {D^{{b{\# 3}g},1} + D^{{b{\# 3}g},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 17\text{-}3g} \right)\end{matrix}$

At this time, X(D) is a polynomial representation of data (information)X and P(D) is a parity polynomial representation. Here, in equations17-1 to 17-3g, parity check polynomials are assumed such that there arethree terms in X(D) and P(D) respectively. In an LDPC-CC of a timevarying period of 3g and a coding rate of 1/2 (n=2), the parity part andinformation at time i are represented by Pi and X_(i,1) respectively. Ifi %3g=k (where k=0, 1, 2, . . . , 3g−1) is assumed at this time, aparity check polynomial of equation 17−(k+1) holds true. For example, ifi=2, i %3g=2 (k=2), and therefore equation 18 holds true.[18](D ^(a#3,1,1) +D ^(a#3,1,2) +D ^(a#3,1,3))X _(2,1)+(D ^(b#3,1) +D^(b#3,2)+1)P ₂=0  (Equation 18)

If <Condition #3-1> and <Condition #4-1> are satisfied at this time, thepossibility of being able to create a code having higher errorcorrection capability is increased.

<Condition #3-1>

In equations 17-1 to 17-3g, combinations of degrees of X(D) satisfy thefollowing condition:

(a_(#1,1,1)%3, a_(1,1,2)%3, a_(1,1,3)%3) are any of (0, 1, 2), (0, 2,1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0);

(a_(#2,1,1)%3, a_(1,1,2)%3, a_(1,1,3)%3) are any of (0, 1, 2), (0, 2,1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0);

(a_(#3,1,1)%3, a_(#1,1,2)%3, a_(#1,1,3)%3) are any of (0, 1, 2), (0, 2,1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0);

-   -   

(a_(#k,1,1)%3, a_(#k,1,2)%3, a_(#k,1,3)%3) are any of (0, 1, 2), (0, 2,1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0);

-   -   

(a_(#3g−2,1,1)%3, a_(#3g−2,1,2)%3, a_(#3g−2,1,3)%3) are any of (0, 1,2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0);

(a_(#3g−1,1,1)%3, a_(#3g−1,1,2)%3, a_(#3g−1,1,3)%3) are any of (0, 1,2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0); and

(a_(#3g,1,1)%3, a_(#3g,1,2)%3, a_(#3g,1,3)%3) are any of (0, 1, 2), (0,2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), or (2, 1, 0).

In addition, in equations 17-1 to 17-3g, combinations of degrees of P(D)satisfy the following condition:

(b_(#1,1)%3, b_(#1,2)%3), (b_(#2,1)%3, b_(#2,2)%3), (b_(#3,1)%3,b_(#3,2)%3), . . . , (b_(#k,1)%3, b_(#k2)%3), . . . , (b_(#3g−2,1)%3,b_(#3g−2,2)%3), (b_(#3g−1,1)%3, b_(#3g−1,2)%3), and (b_(#3g,1)%3.b_(#3g,2)%3) are any of (1, 2), or (2, 1) (k=1, 2, 3, . . . , 3g).

<Condition #3-1> has a similar relationship with respect to equations17-1 to 17-3g as <Condition #2-1> has with respect to equations 15-1 to15-3g. If the condition below (<Condition #4-1>) is added for equations17-1 to 17-3g in addition to <Condition #3-1>, the possibility of beingable to create an LDPC-CC having higher error correction capability isincreased.

<Condition #4-1>

Degrees of P(D) of equations 17-1 to 17-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (b_(#k,1)%3g, b_(#1,2)%3g),(b_(#k,2)%3g, b_(#2,2)%3g), (b_(#3,1)%3g, b_(#3,2)%3g), . . . ,(b_(#k,1)%3g, b_(#k,2)%3g), . . . , (b_(#3g−2,1)%3g, b_(#g−2,2)%3g),(b_(#3g−1,1)%3g, b_(#3g−1,2)%3g), and (b_(#3g,1)%3g, b_(#3g,2)%3g).

The possibility of obtaining good error correction capability is high ifthere is also randomness while regularity is maintained for positions atwhich 1's are present in a parity check matrix. With an LDPC-CC forwhich the time varying period is 3g (where g=2, 3, 4, 5, . . . ) and thecoding rate is 1/2 (n=2) that has parity check polynomials of equations17-1 to 17-3g, if a code is created in which <Condition #4-1> is appliedin addition to <Condition #3-1>, it is possible to provide randomnesswhile maintaining regularity for positions at which 1's are present in aparity check matrix, and therefore the possibility of obtaining bettererror correction capability is increased.

Next, an LDPC-CC of a time varying period of 3g (where g=2, 3, 4, 5, . .. ) is considered that enables encoding to be performed easily andprovides relevancy to parity bits and data bits of the same point intime. At this time, if the coding rate is 1/2 (n=2), LDPC-CC paritycheck polynomials can be represented as shown below.

$\begin{matrix}{\mspace{79mu}\lbrack 19\rbrack} & \; \\{{{\left( {D^{{a{\# 1}},1,1} + D^{{a{\# 1}},1,2} + 1} \right){X(D)}} + {\left( {D^{{b{\# 1}},1} + D^{{b{\# 1}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 19\text{-}1} \right) \\{{{\left( {D^{{a{\# 2}},1,1} + D^{{a{\# 2}},1,2} + 1} \right){X(D)}} + {\left( {D^{{b{\# 2}},1} + D^{{b{\# 2}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 19\text{-}2} \right) \\{{{\left( {D^{{a{\# 3}},1,1} + D^{{a{\# 3}},1,2} + 1} \right){X(D)}} + {\left( {D^{{b{\# 3}},1} + D^{{b{\# 3}},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 19\text{-}3} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{a\# k},1,1} + D^{{a\# k},1,2} + 1} \right){X(D)}} + {\left( {D^{{b\# k},1} + D^{{b\# k},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 19\text{-}k} \right) \\{\mspace{79mu}\vdots} & \; \\{{{\left( {D^{{{a{\# 3}g} - 2},1,1} + D^{{{a{\# 3}g} - 2},1,2} + 1} \right){X(D)}} + {\left( {D^{{{b{\# 3}g} - 2},1} + D^{{{b{\# 3}g} - 2},2} + 1} \right){P(D)}}} = 0} & {\left( {{Equation}\mspace{14mu} 19\text{-}\left( {3g\text{-}2} \right)} \right)\mspace{14mu}} \\{{{\left( {D^{{{a{\# 3}g} - 1},1,1} + D^{{{a{\# 3}g} - 1},1,2} + 1} \right){X(D)}} + {\left( {D^{{{b{\# 3}g} - 1},1} + D^{{{b{\# 3}g} - 1},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 19\text{-}\left( {3g\text{-}1} \right)} \right) \\{{{\left( {D^{{a{\# 3}g},1,1} + D^{{a{\# 3}g},1,2} + 1} \right){X(D)}} + {\left( {D^{{b{\# 3}g},1} + D^{{b{\# 3}g},2} + 1} \right){P(D)}}} = 0} & \left( {{Equation}\mspace{14mu} 19\text{-}3g} \right)\end{matrix}$

At this time, X(D) is a polynomial representation of data (information)X and P(D) is a parity polynomial representation. In equations 19-1 to19-3g, parity check polynomials are assumed such that there are threeterms in X(D) and P(D) respectively, and a D⁰ term is present in X(D)and P(D) (where k=1, 2, 3, . . . , 3g).

In an LDPC-CC of a time varying period of 3g and a coding rate of 1/2(n=2), the parity part and information at time i are represented by Piand X_(i,i) respectively. If i %3g=k (where k=0, 1, 2, . . . , 3g−1) isassumed at this time, a parity check polynomial of equation 19−(k+1)holds true. For example, if i=2, i %3g=2 (k=2), and therefore equation20 holds true.[20](D ^(a#3,1,1) +D ^(a#3,1,2)+1)X _(2,1)+(D ^(b#3,1) +D ^(b#3,2)+1)P₂=0  (Equation 20)

If following <Condition #5-1> and <Condition #6-1> are satisfied at thistime, the possibility of being able to create a code having higher errorcorrection capability is increased.

<Condition #5-1>

In equations 19-1 to 19-3g, combinations of degrees of X(D) satisfy thefollowing condition:

(a_(#1, 1, 1)%3, a_(#1,1,2)%3) is (1, 2) or (2, 1);

(a_(#2,1,1)%3, a_(#2,1,2)%3) is (1, 2) or (2, 1);

(a_(#3,1,1)%3, a_(#3,1,2)%3) is (1, 2) or (2, 1);

-   -   

(a_(#k,1,1)%3, a_(#k,1,2)%3) is (1, 2) or (2, 1) (where k=1, 2, 3, . . ., 3g);

-   -   

(a_(#3g−2,1,1)%3, a_(#3g−2,1,2)%3) is (1, 2) or (2, 1),

(a_(#3g−1,1,1)%3, a_(#3g−1,1,2)%3) is (1, 2) or (2, 1); and

(a_(#3g,1,1)%3, a_(#3g,1,2)%3) is (1, 2) or (2, 1).

In addition, in equations 19-1 to 19-3g, combinations of degrees of P(D)satisfy the following condition:

(b_(#1,1)%3, b_(#1,2)%3), (b_(#2,1)%3, b_(#2,2)%3), (b_(#3,1)%3,b_(#3,2)%3), . . . , (b_(#k,1)%3, b_(#k,2)%3), . . . , (b_(#3g−2,1)%3,b_(#3g−2,2)%3), (b_(#3g−1,1)%3, b_(#3g−1,2)%3), and (b_(#3g,1)%3,b_(#3g,2)%3) are any of (1, 2), or (2, 1) (where k=1, 2, 3, . . . , 3g).

<Condition #5-1> has a similar relationship with respect to equations19-1 to 19-3g as <condition #2-1> has with respect to equations 15-1 to15-3g. If the condition below (<condition #6-1>) is added for equation19-1 to 19-3g in addition to <condition #5-1>, the possibility of beingable to create an LDPC-CC having higher error correction capability isincreased.

<Condition #6-1>

Degrees of X(D) of equations 19-1 to 19-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1, 1, 1)%3g,a_(#1,1,2)%3g), (a_(#2,1,1)%3g, a_(#2,1,2)%3g), . . . , (a_(#p,1,1)%3g,a_(#p,1,2)%3g), . . . , (a_(#3g,1,1)%3g, a_(#3g,1,2)%3g) (where p=1, 2,3, . . . , 3g); and

Degrees of P(D) of equations 19-1 to 19-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (b_(#1,1)%3g, b_(#1,2)%3g),(b_(#2,1)%3g, b_(#2,2)%3g), (b_(#3,1)%3g, b_(#3,2)%3g), . . . ,(b_(#k,1)%3g, b_(#k,2)%3g), . . . , (b_(#3g−2,1)%3g, b_(#3g−2,2)%3g),(b_(#3g−1,1)%3g, b_(#3g−1,2)%3g), and (b_(#3g,1)%3g, b_(#3g,2)%3g)(where k=1, 2, 3, . . . , 3g).

The possibility of obtaining good error correction capability is high ifthere is also randomness while regularity is maintained for positions atwhich 1's are present in a parity check matrix. With an LDPC-CC forwhich the time varying period is 3g (where g=2, 3, 4, 5, . . . ) and thecoding rate is 1/2 that has parity check polynomials of equations 19-1to 19-3g, if a code is created in which <Condition #6-1> is applied inaddition to <Condition #5-1>, it is possible to provide randomness whilemaintaining regularity for positions at which 1's are present in aparity check matrix, so that the possibility of obtaining better errorcorrection capability is increased.

The possibility of being able to create an LDPC-CC having higher errorcorrection capability is also increased if a code is created using<Condition #6′-1> instead of <Condition #6-1>, that is, using <Condition#6′-1> in addition to <Condition #5-1>.

<Condition #6′-1>

Degrees of X(D) of equations 19-1 to 19-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (a_(#1, 1, 1)%3g,a_(#1,1,2)%3g), (a_(#2,1,1)%3g, a_(#2,1,2)%3g), . . . , (a_(#p,1,1)%3g,a_(#p,1,2)%3g), . . . , and (a_(#3g,1,1)%3g, a_(#3g,1,2)%3g) (where p=1,2, 3, . . . , 3g); or

degrees of P(D) of equations 19-1 to 19-3g satisfy the followingcondition:

all values other than multiples of 3 (that is, 0, 3, 6, . . . , 3g−3)from among integers from 0 to 3g−1 (0, 1, 2, 3, 4, . . . , 3g−2, 3g−1)are present in the following 6g values of (b_(#1,1)%3g, b_(#1,2)%3g),(b_(#2,1)%3g, b_(#2,2)%3g), (b_(#3,1)%3g, b_(#3,2)%3g), . . . ,(b_(#k,1)%3g, b_(#k,2)%3g), . . . , (b_(#3g−2,1)%3g, b_(#3g−2,2)%3g),(b_(#3g−1,1)%3g, b_(#3g−1,2)%3g) and (b_(#3g,1)%3g, b_(#3g,2)%3g) (wherek=1, 2, 3, . . . , 3g).

An LDPC-CC of a time varying period of g with good characteristics hasbeen described above. When the above LDPC-CC is used for the erasurecorrection encoding section of Embodiment 1, it has been confirmed thatthe characteristics are further improved if there is no loop 4 (circularpath (circulating path) starting from a certain node and ending at thenode, having a length of 4) or no loop 6 (loop having a length of 6,also referred to as “girth 6”) when a Tanner graph is drawn.

Also, for an LDPC-CC, it is possible to provide encoded data (codeword)by multiplying information vector n by generator matrix G. That is,encoded data (codeword) c can be represented as c=n×G. Here, generatormatrix G is found based on parity check matrix H designed in advance. Tobe more specific, generator matrix G refers to a matrix satisfyingG×H^(T)=0.

For example, a convolutional code of a coding rate of 1/2 and generatorpolynomial G=[1 G₁(D)/G₀(D)] will be considered as an example. At thistime, G represents a feed-forward polynomial and G₀ represents afeedback polynomial. If a polynomial representation of an informationsequence (data) is X(D), and a polynomial representation of a paritysequence is P(D), a parity check polynomial is represented as shown inequation 21 below.[21]G ₁(D)X(D)+G ₀(D)P(D)=0  (Equation 21)

where D is a delay operator.

FIG. 18 shows information relating to a (7,5) convolutional code. A(7,5) convolutional code generator matrix is represented by G=[1(D²+1)/(D²+D+1)]. Therefore, a parity check polynomial is as shown inequation 22 below.[22](D ²+1)X(D)+(D ² +D+1)P(D)=0  (Equation 22)

Here, data at point in time i is represented by X_(i), and parity partby P_(i), and transmission sequence W_(i) is represented byW_(i)=(X_(i), P_(i)). Then, transmission vector w is represented byw=(X₁, P₁, X₂, P₂, . . . , X_(i), P_(i) . . . )^(T). Thus, from equation22, parity check matrix H can be represented as shown in FIG. 18. Atthis time, the relational equation in equation 23 below holds true.Hw=0  (Equation 23)

Therefore, with parity check matrix H, the decoding side can performdecoding using BP (belief propagation) decoding, min-sum decoding whichapproximates BP decoding, offset BP decoding, normalized BP decoding,shuffled BP decoding, as shown in Non-Patent Literature 4 to Non-PatentLiterature 9.

(Time-invariant/time varying LDPC-CCs (of a coding rate of (n−1)/n)based on a convolutional code (where n is a natural number))

An overview of time-invariant/time varying LDPC-CCs based on aconvolutional code is given below.

A parity check polynomial represented as shown in equation 24 will beconsidered, with polynomial representations of a coding rate ofR=(n−1)/n as information X₁, X₂, . . . , X_(n−1) as X₁(D), X₂(D), . . ., X_(n−1)(D), and a parity polynomial representation P as P(D).[24](D ^(a) ^(1,1) +D ^(a) ^(1,2) + . . . +D ^(a) ^(1,r1) +1)X ₁(D)+(D ^(a)^(2,1) +D ^(a) ^(2,2) + . . . +D ^(a) ^(2,r2+1) )X ₂(D)+(D ^(b) ¹ +D^(b) ² + . . . +D ^(b) ¹ +1)P(D)=0  (Equation 24)

In equation 24, at this time, a_(p,p) (where p=1, 2, . . . , n−1 andq=1, 2, . . . , rp) is, for example, a natural number, and satisfies thecondition a_(p,1)≠a_(p,2)≠ . . . ≠a_(p,rp). Also, b_(q) (where q=1, 2, .. . , s) is a natural number, and satisfies the condition b₁≠b₂≠ . . .≠b₅. A code defined by a parity check matrix based on a parity checkpolynomial of equation 24 at this time is called a time-invariantLDPC-CC here.

Here, m different parity check polynomials based on equation 24 areprovided (where m is an integer equal to or greater than 2). Theseparity check polynomials are represented as shown below.[25]A _(X1,j)(D)X ₁(D)+A _(X2,i)(D)X ₂(D)+ . . . +A _(Xn−1,j)(D)X_(n−1)(D)+B _(i)(D)P(D)=0  (Equation 25)In equation 25, i=0, 1, . . . , m−1.

Then in equation 25, information X₁, X₂, . . . , X_(n−1) at point intime j is represented as X_(1,j), X_(2,j), . . . , X_(n−1,j), paritypart P at point in time j is represented as P_(j), and u_(j)=(X_(1,j),X_(2,j), . . . , X_(n−1,j), P_(j))^(T). At this time, informationX_(1,j), X_(2,j), . . . , X_(n−1,j), and parity part P_(j) at point intime j satisfy the parity check polynomial of equation 26.[26]A _(X1,k)(D)X ₁(D)+A _(X2,k)(D)X ₂(D)+ . . . +A _(Xn−1,k)(D)X_(n−1)(D)+B _(k)(D)P(D)=0  (Equation 26)where “j mod m” is the remainder after dividing j by m.

A code defined by a parity check matrix based on the parity checkpolynomial of equation 26 is called a time varying LDPC-CC here. At thistime, the time-invariant LDPC-CC defined by the parity check polynomialof equation 24 and the time varying LDPC-CC defined by the parity checkpolynomial of equation 26 have a characteristic of enabling parity to beeasily found sequentially by means of a register and exclusive OR.

For example, the configuration of parity check matrix H of an LDPC-CC ofa coding rate of 2/3 and of a time varying period of 2 based on equation24 to equation 26 is shown in FIG. 19. Two different check polynomialsof a time varying period of 2 based on equation 26 are designated “checkequation #1” and “check equation #2.” In FIG. 19, (Ha, 111) is a partcorresponding to “check equation #1,” and (Hc,111) is a partcorresponding to “check equation #2.” Below, (Ha, 111) and (Hc, 111) aredefined as sub-matrices.

Thus, LDPC-CC parity check matrix H of a time varying period of 2 ofthis proposal can be defined by a first sub-matrix representing a paritycheck polynomial of “check equation #1,” and by a second sub-matrixrepresenting a parity check polynomial of “check equation #2.”Specifically, in parity check matrix H, a first sub-matrix and secondsub-matrix are arranged alternately in the row direction. When thecoding rate is 2/3, a configuration is employed in which a sub-matrix isshifted three columns to the right between an i'th row and (i+1)-th row,as shown in FIG. 19.

In the case of a time varying LDPC-CC of a time varying period of 2, ani'th row sub-matrix and an (i−1)-th row sub-matrix are differentsub-matrices. That is to say, either sub-matrix (Ha,11) or sub-matrix(Hc, 11) is a first sub-matrix, and the other is a second sub-matrix. Iftransmission vector u is represented as u=(X_(1,0), X_(2,0), P₀,X_(1,1), X_(2,1), P₁, . . . , X_(1,k), X_(2,k), P_(k), . . . )^(T), therelationship Hu=0 holds true.

Next, an LDPC-CC for which the time varying period is m is considered inthe case of a coding rate of 2/3. In the same way as when the timevarying period is 2, m parity check polynomials represented by equation24 are provided. Then “check equation #1” represented by equation 24 isprovided. “Check equation #2” to “check equation #m” represented byequation 24 are provided in a similar way. Data X and parity part P ofpoint in time mi+1 are represented by X_(mi+1) and P_(mi+1)respectively, data X and parity part P of point in time mi+2 arerepresented by X_(mi+2) and P_(mi+2) respectively, . . . , and data Xand parity part P of point in time mi+m are represented by X_(mi+m) andP_(mi+m) respectively (where i is an integer).

Consider an LDPC-CC for which parity P_(mi+1) of point in time mi+1 isfound using “check equation #1,” parity P_(mi+2) of point in time mi+2is found using “check equation #2,” . . . , and parity part P_(mi+m) ofpoint in time mi+m is found using “check equation #m.” An LDPC-CC codeof this kind provides the following advantages:

-   -   An encoder can be configured easily, and a parity part can be        found sequentially.    -   Termination bit reduction and received quality improvement in        puncturing upon termination can be expected.

FIG. 20 shows the configuration of the above LDPC-CC parity check matrixof a coding rate of 2/3 and a time varying period of m. In FIG. 20, (H₁,111) is a part corresponding to “check equation #1,” (H₂, 111) is a partcorresponding to “check equation #2,” . . . , and (H_(m), 111) is a partcorresponding to “check equation #m.” Below, (H₁, 111) is defined as afirst sub-matrix, (H₂, 111) is defined as a second sub-matrix, . . . ,and (H_(m), 111) is defined as an m-th sub-matrix.

Thus, LDPC-CC parity check matrix H of a time varying period of m ofthis proposal can be defined by a first sub-matrix representing a paritycheck polynomial of “check equation #1,” a second sub-matrixrepresenting a parity check polynomial of “check equation #2,” . . . ,and an m-th sub-matrix representing a parity check polynomial of “checkequation #m.” Specifically, parity check matrix H is configured suchthat first to m-th sub-matrix are arranged periodically in the rowdirection (see FIG. 20). When the coding rate is 2/3, a configuration isemployed in which a sub-matrix is shifted three columns to the rightbetween an i-th row and (i+1)-th row (see FIG. 20).

If transmission vector u is represented as u=(X_(1,0), X_(2,0), P₀,X_(1,1), X_(2,1), P₁, . . . , X_(1,k), X_(2,k), P_(k), . . . )^(T), therelationship Hu=0 holds true.

In the above description, a case of a coding rate of 2/3 has beendescribed as an example of a time-invariant/time varying LDPC-CC basedon a convolutional code of a coding rate of (n−1)/n, but atime-invariant/time varying LDPC-CC parity check matrix based on aconvolutional code of a coding rate of (n−1)/n can be created bythinking in a similar way.

The representation method of an LDPC-CC of a time varying period of musing numerical formulas handled in the present specification and therelationship between a parity check polynomial and a parity check matrixwill be described again in Embodiment 5.

That is to say, in the case of a coding rate of 2/3, in FIG. 20,(H₁,111) is a part (first sub-matrix) corresponding to “check equation#1,” (H₂,111) is a part (second sub-matrix) corresponding to “checkequation #2,” . . . , and (H_(m), 111) is a part (m-th sub-matrix)corresponding to “check equation #m,” while, in the case of a codingrate of (n−1)/n, the situation is as shown in FIG. 21. That is to say, apart (first sub-matrix) corresponding to “check equation #1” isrepresented by (H₁, 11 . . . 1), and a part (k-th sub-matrix)corresponding to “check equation #k” (where k=2, 3, . . . , m) isrepresented by (H_(k), 11 . . . 1). At this time, the number of l's ofparts excluding H_(k) in the k-th sub-matrix is n. Also, in parity checkmatrix H, a configuration is employed in which a sub-matrix is shifted ncolumns to the right between an i'th row and (i+1)-th row (see FIG. 21).

If transmission vector u is represented as u=(X_(1,0), X_(2,0), . . . ,X_(n−1,0), P₀, X_(1,1), X_(2,1), . . . , X_(n−1,1), P₁, . . . , X_(1,k),X_(2,k), . . . , X_(n−1,k), P_(k), . . . )^(T), the relationship Hu=0holds true.

FIG. 22 shows an example of the configuration of an LDPC-CC encoder whenthe coding rate is R=1/2. As shown in FIG. 22, LDPC-CC encoder 500 isprovided mainly with data computing section 510, parity computingsection 520, weight control section 530, and mod 2 adder 140.

Data computing section 510 is provided with shift registers 511-1 to511-M and weight multipliers 512-0 to 512-M.

Parity computing section 520 is provided with shift registers 521-1 to521-M and weight multipliers 522-0 to 522-M.

Shift registers 111-1 to 111-M and 521-1 to 521-M are registers storingv_(1,t−i), and v_(2,t−i) (where i=0, . . . , M) respectively, and, at atiming at which the next input comes in, send a stored value to theadjacent shift register to the right, and store a new value sent fromthe adjacent shift register to the left. The initial state of the shiftregisters is all-zeros.

Weight multipliers 512-0 to 512-M and 522-0 to 522-M switch values of h₁^((m)) and h₂ ^((m)) to 0 or 1 in accordance with a control signaloutputted from weight control section 530.

Based on a parity check matrix stored internally, weight control section530 outputs values of h₁ ^((m)) and h₂ ^((m)) at that timing, andsupplies them to weight multipliers 512-0 to 512-M and 522-0 to 522-M.

Mod 2 adder 540 adds all mod 2 computation results to the outputs ofweight multipliers 512-0 to 512-M,522-0 to 522-M, and calculatesv_(2,t).

By employing this kind of configuration, LDPC-CC encoder 500 can performLDPC-CC encoding in accordance with a parity check matrix.

If the arrangement of rows of a parity check matrix stored by weightcontrol section 530 differs on a row-by-row basis, LDPC-CC encoder 500is a time varying convolutional encoder. Also, in the case of an LDPC-CCof a coding rate of (q−1)/q, a configuration needs to be employed inwhich (q−1) data computing sections 510 are provided and mod 2 adder 540performs mod 2 addition of the outputs of weight multipliers.

Embodiment 3

Embodiment 2 has described an LDPC-CC having good characteristics. Thepresent embodiment will describe a shortening method that makes a codingrate variable when the LDPC-CC described in Embodiment 2 is applied to aphysical layer. “Shortening” refers to generating a code of a secondcoding rate from a code of a first coding rate (first coding rate >second coding rate). Hereinafter, a shortening method of generating anLDPC-CC of a coding rate of 1/3 from an LDPC-CC of a coding rate of 1/2will be described as an example.

FIG. 23 shows an example of check equations of an LDPC-CC of a codingrate of 1/2 and parity check matrix H. The LDPC-CC of a coding rate of1/2 shown in FIG. 23 is an example of the LDPC-CC of a time varyingperiod of 3 having good characteristics described in Embodiment 1 andparity check matrix H is made up of equations 27-1 to equation 27-3.[27](D ^(a1) +D ^(a2) +D ^(a3))X(D)+(D ^(b1) +D ^(b2) +D ^(b3))P(D)=(D ² +D¹+1)X(D)+(D ² +D ¹+1)P(D)=0  (Equation 27-1)(D ^(A1) +D ^(A2) +D ^(A3))X(D)+(D ^(B1) +D ^(B2) +D ^(B3))P(D)=(D ⁵ +D¹+1)X(D)+(D ⁵ +D ¹+1)P(D)=0  (Equation 27-2)(D ^(a1) +D ^(a2) +D ^(a3))X(D)+(D ^(B1) +D ^(B2) +D ^(B3))P(D)=(D ⁴ +D²+1)X(D)+(D ⁴ +D ²+1)P(D)=0  (Equation 27-3)

Therefore, equations 27-1 to 27-3 satisfy the condition relating to“remainder” (remainder rule) that “when k is designated as a remainderafter dividing the values of combinations of degrees of X(D) and P(D),(a1, a2, a3), (b1, b2, b3), (A1, A2, A3), (B1, B2, B3), (α1, α2, α3),(β1, β2, β3), in equations 27-1 to 27-3 by 3, provision is made for oneeach of remainders 0, 1, and 2 to be included in three-coefficient setsrepresented as shown above (for example, (a1, a2, a3)), and to hold truewith respect to all of the above three-coefficient sets.”

In FIG. 23, suppose the information and parity part at time i arerepresented by Xi and Pi respectively. If codeword w=(X0, P0, X1, P1, .. . , Xi, Pi, . . . )^(T) is assumed, parity check matrix H and codewordw in FIG. 23 satisfy equation 23. In this case, frame 601 in FIG. 23shows codeword w corresponding to columns of parity check matrix H. Thatis, codeword w has the correspondence with columns of parity checkmatrix H as ( . . . , X_(3k), P_(3k), X_(3k+1), P_(3k+1), X_(3k+2),P_(3k+2), X_(3 (k+1)), P_(3(k+1)), X_(3 (k+1)+1), P_(3(k+1)+1), . . . ).

Hereinafter, a shortening method for realizing a coding rate of 1/3 froman LDPC-CC of a coding rate of 1/2 in a physical layer will bedescribed.

[Method #1-1]

The shortening method inserts known information (e.g. 0's) intoinformation X on a regular basis. For example, known information isinserted into 3 k bits of 6 k bits of information and encoding isapplied to the information of 6k bits including known information usingan LDPC-CC of a coding rate of 1/2. A parity part of 6k bits isgenerated in this way. In this case, the 3k bits of known informationout of the information 6k bits are assumed to be bits not to transmit.This allows a coding rate of 1/3 to be realized.

The known information is not limited to 0, but may be 1 or anypredetermined value other than 1, and needs only to be reported to thecommunication apparatus which is the communicating party in advance ordetermined as a specification.

[Method #1-2]

As shown in FIG. 24, the shortening method assumes 3×2×2k bits made upof information and parity part as one period and inserts knowninformation at each period according to a similar rule (insertion rule).“Inserting known information according to a similar rule (insertionrule)” means inserting known information (e.g. 0 (or 1 or apredetermined value)) in X0, X2, X4 in the first one period when 12 bitsmade up of information and parity part are assumed to be one period asshown in FIG. 25. Positions at which known information is inserted ateach period are equalized such that known information (e.g. 0 (or 1 or apredetermined value)) is inserted in X6, X8, X10 at the next one period,. . . , and known information is inserted in X6i, X6i+2, X6i+4 at ani-th one period.

In the same way as with [method #1-1], for example, known information isinserted in 3k bits of the information 6k bits, encoding is applied tothe information of 6k bits including known information using an LDPC-CCof a coding rate of 1/2, and a parity part of 6k bits is therebygenerated. In this case, if known information of 3k bits is assumed tobe bits not to transmit, a coding rate of 1/3 can be realized.Hereinafter, the relationship between positions at which knowninformation is inserted and error correction capability will bedescribed using FIG. 26A.

FIG. 26A shows the correspondence between a part of parity check matrixH and codeword w (X0, P0, X1, P1, X2, P2, . . . , X9, P9). Elements “1”are arranged in columns corresponding to X₂ and X₄ in row 701 in FIG.26A. Furthermore, elements “1” are arranged in columns corresponding toX2 and X9 in row 702 in FIG. 26A. Therefore, when known information isinserted in X2, X4 and X9, all information corresponding to columnswhose elements are “1” is known in row 701 and row 702. Thus, unknownvalues only correspond to parity part in row 701 and row 702, and it isthereby possible to update a log likelihood ratio with high reliabilityin row computation in BP decoding.

That is, when realizing a coding rate smaller than the original codingrate by inserting known information, it is important, from thestandpoint of obtaining high error correction capability, to increasethe number of rows, all of which correspond to known information orrows, a large number of which correspond to known information (e.g. allbits except one bit correspond to known information) of the informationout of the parity part and information in each row of a parity checkmatrix, that is, parity check polynomial.

In the case of a time-varying LDPC-CC, since there is regularity in apattern of parity check matrix H in which elements “I” are arranged, andtherefore by inserting known information on a regular basis at eachperiod based on parity check matrix H, it is possible to increase thenumber of rows in which unknown values only correspond to parity or rowswith fewer unknown information bits, and thereby obtain an LDPC-CC of acoding rate of 1/3 providing good characteristics.

According to following [method #1-3], it is possible to realize anLDPC-CC having high error correction capability, a coding rate of 1/3and a time varying period of 3 from the LDPC-CC having goodcharacteristics, a coding rate of 1/2, and a time varying period of 3described in Embodiment 2.

The shortening method will be described below which realizes a codingrate of 1/3 from an LDPC-CC of a coding rate of 1/2 and a time varyingperiod of 3 represented by equations 3-1 to 3-3 that satisfy thecondition relating to “remainder” (remainder rule) that “when k isdesignated as a remainder after dividing the values of combinations ofdegrees of X(D) and P(D), (a1, a2, a3), (b1, b2, b3), (A1, A2, A3), (B1,B2, B3), (α1, α2, α3), (β1, β2, β3), in equations 3-1 to 3-3 by 3,provision is made for one each of remainders 0, 1, and 2 to be includedin three-coefficient sets represented as shown above (for example, (a1,a2, a3)), and to hold true with respect to all of the abovethree-coefficient sets.”

[Method #1-3]

The shortening method inserts known information (e.g. 0 (or 1 or apredetermined value)) in 3k Xj's (where j takes any value of 6i to6(i+k−1)+5, and there are 3k different values) out of 6k bits ofinformation X_(6i), X_(6i+1), X_(6i+2), X_(6i+3), X_(6i+4), X_(6i+5), .. . , X_(6 (i+k−1)), X_(6 (i+k−1)+1), X_(6 (i+k−1)+2), X_(6 (i+k−1)+3),X_(6(i+k−1)+4), X_(6(i+k−1)+5) at periods of 3×2×2k bits made up ofinformation and parity part.

In this case, when known information is inserted in 3k Xj's, provisionis made such that, of the remainders after dividing 3k different j's by3, the number of remainders which become 0 is k, the number ofremainders which become 1 is k and the number of remainders which become2 is k.

By this means, by providing a condition for positions at which knowninformation is inserted, it is possible to increase, as much aspossible, the number of rows in which all information is knowninformation or rows having many pieces of known information (e.g. allbits except one bit correspond to known information) in each row ofparity check matrix H, that is, a parity check polynomial. This will bedescribed below.

It is assumed that the LDPC-CC of a coding rate of 1/2 and a timevarying period of 3 shown in equations 3-1 to 3-3 is designed based on acondition relating to “remainder” (remainder rule). That is, assume thatequations 3-1 to 3-3 satisfy the condition relating to “remainder”(remainder rule) that “when k is designated as a remainder afterdividing the values of combinations of degrees of X(D) and P(D), (a1,a2, a3), (b1, b2, b3), (A1, A2, A3), (B1, B2, B3), (α1, α2, α3), (β1,β2, β3), in equations 3-1 to 3-3 by 3, provision is made for one each ofremainders 0, 1, and 2 to be included in three-coefficient setsrepresented as shown above (for example, (a1, a2, a3)), and to hold truewith respect to all of the above three-coefficient sets.”

FIG. 26B shows the correspondence between a parity check matrix of anLDPC-CC of a coding rate of 1/2 and a time varying period of 3 thatsatisfies the above remainder rule and points in time. The parity checkmatrix in FIG. 26B is an example where check equation #1 is parity checkpolynomial 27-1, check equation #2 is parity check polynomial 27-2 andcheck equation #3 is parity check polynomial 27-3.

As shown in FIG. 26B, elements corresponding to information at point intime j, point in time (j−1) and point in time (j−2) in equation 27-1 are1's. Therefore, 0, 1 and 2 are present at points in time at whichelements “1” in equation 27-1 are present, that is, in remainders afterdividing values of (j, (j−1), (j−2)) by 3, regardless of the value of j.0, 1 and 2 are present in the remainders after dividing values of (j,(j−1), (j−2)) by 3, regardless of the value of j in this way becauseequation 27-1 satisfies the above remainder rule.

Similarly, since parity check polynomial 27-2 also satisfies the aboveremainder rule, 0, 1 and 2 are present at points in time at whichelements “1” in equation 27-2 are present, that is, in remainders afterdividing values of (j, (j−1), (j−5)) by 3, regardless of the value of j.

Similarly, since parity check polynomial 27-3 also satisfies the aboveremainder rule, 0, 1 and 2 are present at points in time at whichelements “1” in equation 27-3 are present, that is, in remainders afterdividing values of (j, (j−2), (j−4)) by 3, regardless of the value of j.

As described above, in parity check matrix H, the greater the number ofrows in which all information corresponding to columns whose elementsare 1's becomes known information or information corresponding tocolumns whose elements are 1's becomes known information, the higher isthe reliability with which a high log likelihood ratio can be updated inrow computation in BP decoding. Therefore, when realizing a coding rateof 1/3 by inserting known information in 3k bits of information 6k bitsin a period of 3×2×2k bits made up of information and parity part, wheninformation at point in time j is represented by Xj, if the number ofremainders after dividing j by 3 which become 0, the number ofremainders which become 1 and the number of remainders which become 2are the same, it is possible, when the characteristics of aboveequations 27-1, 27-2 and 27-3 are taken into account, to increase thenumber of rows in which all information corresponding to columns whoseelements are 1's becomes known information or rows in which informationcorresponding to columns whose elements are 1's becomes knowninformation.

Thus, the insertion rule according to [method #1-3] focusing on thenumber of remainders is important in creating an LDPC-CC of a codingrate of 1/3 and a time varying period of 3 having high error correctioncapability from an LDPC-CC of a coding rate of 1/2 and a time varyingperiod of 3 created based on the remainder rule.

This will be described returning to FIG. 25 again. As shown in FIG. 25,assuming 3×2×2×1 bits (that is, k=1) to be one period, consider a casewhere known information (e.g. 0 (or 1 or a predetermined value)) isinserted in X_(6i), X_(6i+2), X_(6i+4) of information and parity partX_(6i), P_(6i), X_(6i+1), P_(6i+1), X_(6i+2), P_(6i+2), X_(6i+3),P_(6i+3), X_(6i+4), P_(6i+4), X_(6i+5), P_(6i+5).

In this case, as j of Xj in which known information is inserted, thereare three different values of 6i, 6i+2 and 6i+4. In this case, theremainder after dividing 6i by 3 is 0, the remainder after dividing 6i+2by 3 is 2 and the remainder after dividing 6i+4 by 3 is 1. Therefore,the number of remainders which become 0 is 1, the number of remainderswhich become 1 is 1 and the number of remainders which become 2 is 1,which satisfies the insertion rule of above [method #1-3]. Thus, theexample shown in FIG. 25 can be said to be an example satisfying theinsertion rule of above [method #1-3].

On the other hand, when the insertion rule of above [method #1-3] is notsatisfied as described above, the number of rows in which unknown valuesonly correspond to parity part decreases. Thus, the insertion rule of[method #1-3] becomes important in shortening an LDPC-CC of a codingrate of 1/2 that satisfies the condition relating to “remainder”(remainder rule) and acquiring an LDPC-CC of a coding rate of 1/3 andhaving good characteristics.

Next, a shortening method will be described which realizes a coding ratesmaller than coding rate (n−1)/n from the LDPC-CC of a coding rate(n−1)/n (n is an integer equal to or greater than 2) and a time varyingperiod of 3 described in Embodiment 2.

An overview of an LDPC-CC of a coding rate of (n−1)/n and a time varyingperiod of 3 capable of obtaining good characteristics is given below.

Consider above equations 4-1 to 4-3 as parity check polynomials of anLDPC-CC for which the coding rate is (n−1)/n and the time varying periodis 3. In this case, X₁(D), X₂(D), . . . , X_(n−1)(D) is a polynomialrepresentation of data (information) X₁, X₂, . . . , X_(n−1) and P(D) isa parity polynomial representation. Here, in equations 4-1 to 4-3,parity check polynomials are assumed such that there are three terms inX₁(D), X₂(D), . . . , X_(n−1)(D) and P(D) respectively.

In equation 4-1, it is assumed that a_(i,1), a_(i,2), and a_(i,3) (wherei=1, 2, . . . , n−1) are integers (where a_(i,1)≠a_(i,2)≠a_(i,3)). Also,it is assumed that b1, b2 and b3 are integers (where b1≠b2≠b3). A paritycheck polynomial of equation 4-1 is called “check equation #1.” Asub-matrix based on the parity check polynomial of equation 4-1 isdesignated first sub-matrix H₁.

Furthermore, in equation 4-2, it is assumed that A_(i,1), A_(i,2), andA_(i,3) (where i=1, 2, . . . , n−1) are integers (whereA_(i,1)≠A_(i,2)≠A_(i,3)). Also, it is assumed that B1, B2 and B3 areintegers (where B1≠B2≠B3). A parity check polynomial of equation 4-2 iscalled “check equation #2.” A sub-matrix based on the parity checkpolynomial of equation 4-2 is designated second sub-matrix H₂.

Furthermore, in equation 4-3, it is assumed that α_(i,1), α_(i,2),α_(i,3) (where i=1, 2, . . . , n−1) are integers (whereα_(i,1)≠α_(i,2)≠α_(i,3)). Also, it is assumed that β1, β2 and β3 areintegers (where β1≠β2≠β3). A parity check polynomial of equation 4-3 iscalled “check equation #3.” A sub-matrix based on the parity checkpolynomial of equation 4-3 is designated third sub-matrix H₃.

Next, an LDPC-CC of a time varying period of 3 generated from firstsub-matrix H₁, second sub-matrix H₂ and third sub-matrix H₃ isconsidered.

At this time, if k is designated as a remainder after dividing thevalues of combinations of degrees of X₁(D), X₂(D), . . . , X_(n−1)(D),and P(D), (a_(1,1), a_(1,2), a_(1,3)), (a_(2,1), a_(2,2), a_(2,3)), . .. , (a_(n−1,1), a_(n−1,2), a_(n−1,3)), (b1, b2, b3), (A_(1,1), A_(1,2),A_(1,3)), (A_(2,1), A_(2,2), A_(2,3)), . . . , (A_(n−1,1), A_(n−1,2),A_(n−1,3)), (B1, B2, B3), (α_(1,1), α_(1,2), α_(1,3)), (α_(2,1),α_(2,2), α_(2,3)), . . . , (α_(n−1,1), α_(n−1,2), a_(n−1,3)), (β1, β2,β3), in equations 4-1 to 4-3 by 3, provision is made for one each ofremainders 0, 1, and 2 to be included in three-coefficient setsrepresented as shown above (for example, (a_(1,1), a_(1,2), a_(1,3))),and to hold true with respect to all of the above three-coefficientsets.

That is to say, provision is made for (a_(1,1)%3, a_(1,2)%3, a_(1,3)%3),(a_(2,1)%3, a_(2,2)%3, a_(2,3)%3), . . . , (a_(n−1,1)%3, a_(n−1,2)%3,a_(n−1,3)%3), (b1%3, b2%3, b3%3), (A_(1,1),%3, A_(1,2)%3, A_(1,3)%3),(A_(2,1)%3, A_(2,2)%3, A_(2,3)%3), . . . , (A_(n−1,1)%3, A_(n−1,2)%3,A_(n−1,3)%3), (B1%3, B2%3, B3%3), (α_(1,1)%3, α_(1,2)%3, α_(1,3)%3),(α_(2,1)%3, α_(2,2)%3, α_(2,3)%3), . . . , (α_(n−1,1)%3, α_(n−1,2)%3,α_(n−1,3)%3) and (β1%3, β2%3, β3%3) to be any of the following: (0, 1,2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), (2, 1, 0).

Generating an LDPC-CC in this way enables a regular LDPC-CC code to begenerated. Furthermore, when BP decoding is performed, belief in “checkequation #2” and belief in “check equation #3” are propagated accuratelyto “check equation #1,” belief in “check equation #1” and belief in“check equation #3” are propagated accurately to “check equation #2,”and belief in “check equation #1” and belief in “check equation #2” arepropagated accurately to “check equation #3.” Consequently, an LDPC-CCwith better received quality can be obtained in the same way as in thecase of a coding rate of 1/2.

The shortening method for realizing a coding rate smaller than a codingrate of (n−1)/n having high error correction capability using the aboveLDPC-CC of a coding rate of (n−1)/n and a time varying period of 3 is asshown below.

[Method #2-1]

The shortening method inserts known information (e.g. 0 (or 1 or apredetermined value)) in information X on a regular basis.

[Method #2-2]

As shown in FIG. 27, the shortening method assumes 3×n×k bits made up ofinformation and parity part as one period and inserts known informationat each period in accordance with a similar rule (insertion rule).“Inserting known information in accordance with a similar rule(insertion rule)” at each period is as described in above [method #1-2]using FIG. 25.

[Method #2-3]

The shortening method selects Z bits from 3×n×k bits of informationX_(0,3i), X_(1,3i), X_(2,3i), . . . , X_(n−1,3i), . . . ,X_(0,3(i+k−1)+2), X_(1,3(i+k−1)+2), X_(2,3(i+k−1)+2), . . . ,X_(n−1,3(i+k−1)+2) at a period of 3×n×k bits made up of information andparity part and inserts known information (e.g. 0 (or 1 or apredetermined value)) in the selected Z bits.

In this case, the shortening method calculates remainders after dividingX_(0,j) (where j takes a value of any of 3i to 3(i+k−1)+2) into whichknown information is inserted by 3 for all j's. Then, provision is madesuch that the difference between the number of remainders which become 0and the number of remainders which become 1 is 1 or less, the differencebetween the number of remainders which become 0 and the number ofremainders which become 2 is 1 or less and the difference between thenumber of remainders which become 1 and the number of remainders whichbecome 2 is 1 or less.

Similarly, the shortening method calculates remainders after dividingX_(1,j) (where j takes a value of any of 3i to 3(i+k−1)+2) into whichknown information is inserted by 3 for all j's. Then, provision is madesuch that the difference between the number of remainders which become 0and the number of remainders which become 1 is 1 or less, the differencebetween the number of remainders which become 0 and the number ofremainders which become 2 is 1 or less and the difference between thenumber of remainders which become 1 and the number of remainders whichbecome 2 is 1 or less.

Similarly, the shortening method calculates remainders after dividingX_(h,j) (where j takes a value of any of 3i to 3(i+k−1)+2) into whichknown information is inserted by 3 for all j's. Then, provision is madesuch that the difference between the number of remainders which become 0and the number of remainders which become 1 is 1 or less, the differencebetween the number of remainders which become 0 and the number ofremainders which become 2 is 1 or less and the difference between thenumber of remainders which become 1 and the number of remainders whichbecome 2 is 1 or less (h=1, 2, 3, . . . , n−1).

By providing a condition for positions at which known information isinserted in this way, it is possible to generate more “rows in whichunknown values only correspond to parity part and with fewer informationbits” in parity check matrix H in the same way as with [method #1-3] andthereby realize a coding rate smaller than a coding rate of (n−1)/nhaving high error correction capability using the aforementioned LDPC-CCof a coding rate of (n−1)/n and a time varying period of 3 having goodcharacteristics.

A case has been described in [method #2-3] where the number of pieces ofknown information inserted is the same at all periods, but the number ofpieces of known information inserted may vary from one period toanother. For example, as shown in FIG. 28, No pieces of information maybe designated known information at a first period, N₁ pieces ofinformation may be designated known information at the next period andNi pieces of information may be designated known information at an i-thperiod. Thus, when the number of pieces of known information inserteddiffers from one period to another, the concept of “period” holds novalid meaning. According to the shortening method, when [method #2-3] isrepresented without using the concept of “period,” it is represented as[method #2-4].

[Method #2-4]

This method selects Z bits from a bit sequence of information X_(0,0),X_(1,0), X_(2,0), . . . , X_(n−1,0), . . . X_(0,v), X_(1,v), X_(2,v), .. . , X_(n−1,v) in a data sequence made up of information and paritypart and inserts known information (e.g. 0 (or 1 or a predeterminedvalue)) into the selected Z bits.

In this case, the shortening method calculates a remainder afterdividing X_(0,j) (where j takes a value of any of 0 to v) into whichknown information is inserted by 3 for all j's. Then, provision is madesuch that the difference between the number of remainders which become 0and the number of remainders which become 1 is 1 or less, the differencebetween the number of remainders which become 0 and the number ofremainders which become 2 is 1 or less and the difference between thenumber of remainders which become 1 and the number of remainders whichbecome 2 is 1 or less.

Similarly, the shortening method calculates remainders after dividingX_(1,j) (where j takes a value of any of 0 to v) into which knowninformation is inserted by 3 for all j's. Then, provision is made suchthat the difference between the number of remainders which become 0 andthe number of remainders which become 1 is 1 or less, the differencebetween the number of remainders which become 0 and the number ofremainders which become 2 is 1 or less and the difference between thenumber of remainders which become 1 and the number of remainders whichbecome 2 is 1 or less.

Similarly, the shortening method calculates remainders after dividingX_(h,j) (where j takes a value of any of 0 to v) into which knowninformation is inserted by 3 for all j's. Then, provision is made suchthat the difference between the number of remainders which become 0 andthe number of remainders which become 1 is 1 or less, the differencebetween the number of remainders which become 0 and the number ofremainders which become 2 is 1 or less and the difference between thenumber of remainders which become 1 and the number of remainders whichbecome 2 is 1 or less (h=1, 2, 3, . . . , n−1).

By providing a condition for positions at which known information isinserted in this way, it is possible to generate more “rows in whichunknown values correspond to parity part and with fewer informationbits” in parity check matrix H even when the number of bits of knowninformation inserted differs from one period to another (or, when thereis no such concept as “period”) in the same way as with [method #2-3]and thereby realize a coding rate smaller than a coding rate of (n−1)/nhaving high error correction capability using the aforementioned LDPC-CCof a coding rate of (n−1)/n and a time varying period of 3 having goodcharacteristics.

The shortening method described so far is a shortening method whichmakes a coding rate variable in the physical layer. For example, acommunication apparatus inserts information known to a communicatingparty, performs encoding at a coding rate of 1/2 on informationincluding known information and generates parity bits. The communicationapparatus then transmits not the known information but information otherthan the known information and the parity bits obtained, and therebyrealizes a coding rate of 1/3.

An LDPC-CC of a time varying period of 3 has been described above as anexample, but it is possible to realize an error correction method havinghigh error correction capability also for the LDPC-CCs of a time varyingperiod of 3g (g=1, 2, 3, 4, . . . ) having good characteristicsdescribed in Embodiment 2 (that is, LDPC-CCs whose time varying periodis multiples of 3) in the same way as the LDPC-CCs of a time varyingperiod of 3 by satisfying above [method #1-1] to [method #1-3] or[method #2-1] to [method #2-4].

FIG. 29A is a block diagram illustrating an example of the configurationrelating to encoding when a coding rate in a physical layer is madevariable.

Known information insertion section 131 receives information 801 andcontrol signal 802 as input and inserts known information according toinformation of a coding rate included in control signal 802. To be morespecific, when the coding rate included in control signal 802 is smallerthan a coding rate supported by encoder 132 and requires shortening,known information insertion section 131 inserts known informationaccording to the above shortening method and outputs information 804after inserting the known information. On the other hand, when thecoding rate included in control signal 802 is equal to the coding ratesupported by encoder 132 and requires no shortening, known informationinsertion section 131 does not insert known information and outputsinformation 801 as information 804 as is.

Encoder 132 receives information 804 and control signal 802 as input,performs encoding on information 804, generates parity part 806 andoutputs parity part 806.

Known information deleting section 133 receives information 804 andcontrol signal 802 as input, deletes, when known information is insertedby known information insertion section 131, the known information frominformation 804 based on information on a coding rate included incontrol signal 802 and outputs information 808 after the deletion. Onthe other hand, when known information is not inserted by knowninformation insertion section 131, known information deleting section133 outputs information 804 as information 808 as is.

Modulation section 141 receives parity part 806, information 808 andcontrol signal 802 as input, modulates parity part 806 and information808 based on information of a modulation scheme included in controlsignal 802, and generates and outputs baseband signal 810.

FIG. 29B is a block diagram illustrating an example of anotherconfiguration of the encoding-related section when the coding rate ismade variable in the physical layer which is different from FIG. 29A. Asshown in FIG. 29B, even if known information deleting section 133 inFIG. 29A is omitted, by adopting a configuration where information 801inputted to known information insertion section 131 is inputted tomodulation section 141, the coding rate can be made variable in the sameway as in FIG. 29A.

FIG. 30 is a block diagram illustrating an example of the configurationof error correcting decoding section 220 in a physical layer. Knowninformation log likelihood ratio insertion section 221 receives loglikelihood ratio signal 901 which is received data and control signal902 as input, inserts, when a log likelihood ratio of known informationneeds to be inserted based on the information of the coding rateincluded in control signal 902, the log likelihood ratio of knowninformation having high reliability into log likelihood ratio signal 901and outputs log likelihood ratio signal 904 after the insertion of thelog likelihood ratio of the known information. The information of thecoding rate included in control signal 902 is transmitted from, forexample, the communicating party.

Decoder 222 receives control signal 902 and log likelihood ratio signal904 after the insertion of the log likelihood ratio of the knowninformation as input, performs decoding based on the information of anencoding method such as a coding rate included in control signal 902,decodes data 906 and outputs decoded data 906.

Known information deleting section 223 receives control signal 902 anddecoded data 906 as input, deletes, when known information is insertedbased on information of an encoding method such as a coding rateincluded in control signal 902, the known information and outputsinformation 908 after the deletion of the known information.

As the shortening method in the physical layer, a shortening method forrealizing a coding rate smaller than the coding rate of a code from theLDPC-CC of a time varying period of 3 described in Embodiment 2 has beendescribed above. Using the shortening method of the present embodimentcan improve transmission efficiency and erasure correction capabilitysimultaneously and obtain good erasure correction capability even whenthe coding rate in the physical layer is changed.

In a convolutional code such as LDPC-CC, a termination sequence may beadded at an end of a transmission information sequence to performtermination, and the termination sequence receives known information(e.g. all 0's) as input and is made up of only a parity sequence.Therefore, there can be some part of the termination sequence that willnot follow the known information insertion rule (insertion rule)described in the invention of the present application. Furthermore, inparts other than termination, there may also be both a part that followsthe insertion rule and a part into which known information is notinserted to improve the transmission rate.

Embodiment 4

The present embodiment will describe a method of changing a coding ratewhen the LDPC-CC of a time varying period of 3 described in Embodiment 2is used for an erasure correction code.

An overview of an LDPC-CC of a coding rate of (n−1)/n and a time varyingperiod of 3 that can obtain good characteristics is given below.

Consider equations 4-1 to 4-3 as parity check polynomials of an LDPC-CCfor which the time varying period is 3. At this time, X₁(D), X₂(D), . .. , X_(n−1)(D) are polynomial representations of data (information) X₁,X₂, . . . , X_(n−1), and P(D) is a parity polynomial representation.Here, in equations 4-1 to 4-3, parity check polynomials are assumed suchthat there are three terms in X₁(D), X₂(D), . . . , X_(n−1)(D), and P(D)respectively.

In equation 4-1, it is assumed that a_(i,1), a_(i,2), and a_(i,3) (wherei=1, 2, . . . , n−1) are integers (where a_(i,1)≠a_(i,2)≠a_(i,3)). Also,it is assumed that b1, b2 and b3 are integers (where b1≠b2≠b3). A paritycheck polynomial of equation 4-1 is called “check equation #1.” Asub-matrix based on the parity check polynomial of equation 4-1 isdesignated first sub-matrix H₁.

In equation 4-2, it is assumed that A_(i,1), A_(i,2), and A_(i,3) (wherei=1, 2, . . . , n−1) are integers (where A_(i,1)≠A_(i,2)≠A_(i,3)). Also,it is assumed that B1, B2 and B3 are integers (where B1≠B2≠B3). A paritycheck polynomial of equation 4-2 is called “check equation #2.” Asub-matrix based on the parity check polynomial of equation 4-2 isdesignated second sub-matrix H₂.

Furthermore, in equation 4-3, it is assumed that α_(i,1), α_(i,2), anda_(i,3) (where i=1, 2, . . . , n−1) are integers (whereα_(i,1)≠a_(i,2)≠α_(i,3)). Also, it is assumed that β1, β2 and β3 areintegers (where β1≠β2≠β3). A parity check polynomial of equation 4-3 iscalled “check equation #3.” A sub-matrix based on the parity checkpolynomial of equation 4-3 is designated third sub-matrix H₃.

Next, an LDPC-CC of a time varying period of 3 generated from firstsub-matrix H₁, second sub-matrix H₂ and third sub-matrix H₃ isconsidered.

At this time, if k is designated as a remainder after dividing thevalues of combinations of degrees of X₁(D), X₂(D), . . . , X_(n−1)(D),and P(D), (a_(1,1), a_(1,2), a_(1,3))), (a_(2,1), a_(2,2), a_(2,3)), . .. , (a_(n−1,1), a_(n−1,2), a_(n−1,3)), (b1, b2, b3), (A_(1,1), A_(1,2),A_(1,3)), (A_(2,1), A_(2,2), A_(2,3)), . . . , (A_(n−1,1), A_(n−1,2),A_(n−1,3)), (B1, B2, B3), (α_(1,1), α_(1,2), α_(1,3)), (α_(2,1),α_(2,2), α_(2,3)), . . . , (α_(n−1,1), α_(n−1,2), α_(n−1,3)), (β1, β2,β3), in equations 4-1 to 4-3 by 3, provision is made for one each ofremainders 0, 1, and 2 to be included in three-coefficient setsrepresented as shown above (for example, (a_(1,1), a_(1,2), a_(1,3))),and to hold true with respect to all of the above three-coefficientsets.

That is to say, provision is made for (a_(1,1)%3, a_(1,2)%3, a_(1,3)%3),(a_(2,1)%3, a_(2,2)%3, a_(2,3)%3), . . . , (a_(n−1,1)%3, a_(n−1,2)%3,a_(n−1,3)%3), (b1%3, b2%3, b3%3), (A_(1,1)%3, A_(1,2)%3, A_(1,3)%3),(A_(2,1)%3, A_(2,2)%3, A_(2,3)%3), . . . , (A_(n−1,1)%3, A_(n−1,2)%3,A_(n−1,3)%3), (B1%3, B2%3, B3%3), (α_(1,1)%3, α_(1,2)%3, α_(1,3)%3),(α_(2,1)%3, α_(2,2)%3, α₂₃%3), . . . , (α_(n−1,1)%3, α_(n−1,2)%3,α_(n−1,3)%3) and (β1%3, β2%3, β3%3) to be any of the following: (0, 1,2), (0, 2, 1), (1, 0, 2), (1, 2, 0), (2, 0, 1), (2, 1, 0).

The erasure correction method for realizing a coding rate smaller than acoding rate of (n−1)/n of high error correction capability using theabove LDPC-CC of a coding rate of (n−1)/n and a time varying period of 3is shown below.

[Method #3-1]

As shown in FIG. 31, assuming 3×n×k bits (k is a natural number) made upof information and parity part as a period, known information includedin a known information packet is inserted at each period in accordancewith a similar rule (insertion rule). “Inserting known informationincluded in a known information packet in accordance with a similar rule(insertion rule) at each period” means equalizing positions at whichknown information is inserted at each period, for example, by insertingknown information included in a known information packet (e.g. 0 (or 1or a predetermined value)) in X0, X2, X4 in the first one period when 12bits made up of information and parity part as shown in FIG. 25 areassumed to be a one period, inserting known information included in theknown information packet (e.g. 0 (or 1 or a predetermined value)) in X6,X8, X10 at the next one period, . . . , inserting known informationincluded in the known information packet in X6i, X6i+2, X6i+4 at an i-thone period, . . .

[Method #3-2]

Z bits are selected from 3×n×k bits of information X_(0,3i), X_(1,3i),X_(2,3i), . . . , X_(n−1,3i), . . . , X_(0,3(i+k−1)+2),X_(1,3(i+k−1)+2), X_(2,3(i+k−1)+2), . . . , X_(n−1,3(i+k−1)+2) at aperiod of 3×n×k bits made up of information and parity part and data(e.g. 0 (or 1 or a predetermined value)) of the known information packetis inserted in the selected Z bits.

In this case, the erasure correction method calculates a remainder whendividing X_(0,j) (where j takes a value of any one of 3i to 3(i+k−1)+2)into which known information included in the known information packet isinserted by 3 for all j's. Then, provision is made such that thedifference between the number of remainders which become 0 and thenumber of remainders which become 1 is 1 or less, the difference betweenthe number of remainders which become 0 and the number of remainderswhich become 2 is 1 or less and the difference between the number ofremainders which become 1 and the number of remainders which become 2 is1 or less.

Similarly, the erasure correction method calculates remainders afterdividing X_(1,j) (where j takes a value of any of 3i to 3(i+k−1)+2) intowhich data of the known information packet is inserted by 3 for all j's.Then, provision is made such that the difference between the number ofremainders which become 0 and the number of remainders which become 1 is1 or less, the difference between the number of remainders which become0 and the number of remainders which become 2 is 1 or less and thedifference between the number of remainders which become 1 and thenumber of remainders which become 2 is 1 or less.

Similarly, the erasure correction method calculates remainders afterdividing X_(h,j) (where j takes a value of any of 3i to 3(i+k−1)+2) intowhich data of the known information packet is inserted by 3 for all j's.Then, provision is made such that the difference between the number ofremainders which become 0 and the number of remainders which become 1 is1 or less, the difference between the number of remainders which become0 and the number of remainders which become 2 is 1 or less and thedifference between the number of remainders which become 1 and thenumber of remainders which become 2 is 1 or less (h=, 2, 3, . . . ,n−1).

By providing a condition for positions at which known information isinserted in this way, it is possible to generate more “rows whoseunknown values correspond to parity part and with fewer informationbits” in parity check matrix H and thereby realize a system having higherasure correction capability and capable of changing a coding rate ofthe erasure correction code with a small circuit scale using theaforementioned LDPC-CC of a coding rate of (n−1)/n and a time varyingperiod of 3 having good characteristics.

An erasure correction method in a upper layer employing a variablecoding rate of the erasure correction code has been described so far.

The configuration of the erasure correction encoding-related processingsection and erasure correction decoding related processing sectionemploying a variable coding rate of the erasure correction code in aupper layer has been described in Embodiment 1. As described inEmbodiment 1, the coding rate of the erasure correction code can bechanged by inserting a known information packet before erasurecorrection encoding-related processing section 120.

This makes it possible to make the coding rate variable according to,for example, a communication situation and thereby increase the codingrate when the communication situation is good and improve transmissionefficiency. Furthermore, when the coding rate is reduced, the erasurecorrection capability can be improved by inserting known informationincluded in a known information packet in accordance with the paritycheck matrix as with [method #3-2].

[method #3-2] has described a case where the number of pieces of data ofa known information packet inserted remains the same for differentperiods, but the number of pieces of data of the known informationpacket inserted may differ from one period to another. For example, asshown in FIG. 32, N₀ pieces of information may be designated data of theknown information packet at a first period, N₁ pieces of information maybe designated data of the known information packet at the next periodand Ni pieces of information may be designated data of the knowninformation packet at an i-th period. Thus, when the number of pieces ofdata of the known information packet inserted differs from one period toanother, the concept of “period” holds no valid meaning. According tothe erasure correction method, when [method #3-2] is represented withoutusing the concept of “period,” it is represented as [method #3-3].

[Method #3-3]

Z bits are selected from a bit sequence of information X_(0,0), X_(1,0),X_(2,0), . . . X_(n−1,0), . . . , X_(0,v), X_(1,v), X_(2,v), . . . ,X_(n−1,v), in a data sequence made up of information and parity part anddata of a known information packet (e.g. 0 (or 1 or a predeterminedvalue)) is inserted.

In this case, the erasure correction method calculates a remainder afterdividing X_(0,j) (where j takes a value of any of 0 to v) into whichdata of the known information packet is inserted by 3 for all j's. Then,provision is made such that the difference between the number ofremainders which become 0 and the number of remainders which become 1 is1 or less, the difference between the number of remainders which become0 and the number of remainders which become 2 is 1 or less and thedifference between the number of remainders which become 1 and thenumber of remainders which become 2 is 1 or less.

Similarly, the erasure correction method calculates remainders afterdividing X_(1,j) (where j takes a value of any of 0 to v) into whichdata of the known information packet is inserted by 3 for all j's. Then,provision is made such that the difference between the number ofremainders which become 0 and the number of remainders which become 1 is1 or less, the difference between the number of remainders which become0 and the number of remainders which become 2 is 1 or less and thedifference between the number of remainders which become 1 and thenumber of remainders which become 2 is 1 or less.

Similarly, the erasure correction method calculates remainders afterdividing X_(h,j) (where j takes a value of any of 0 to v) into whichdata of the known information packet is inserted by 3 for all j's. Then,provision is made such that the difference between the number ofremainders which become 0 and the number of remainders which become 1 is1 or less, the difference between the number of remainders which become0 and the number of remainders which become 2 is 1 or less and thedifference between the number of remainders which become 1 and thenumber of remainders which become 2 is 1 or less (h=1, 2, 3, . . . ,n−1).

A system has been described so far which makes variable a coding rate ofthe erasure correction code using a method of realizing a coding ratesmaller than a coding rate of a code from the LDPC-CC of a time varyingperiod of 3 described in Embodiment 2. Using the variable coding ratemethod according to the present embodiment can improve transmissionefficiency and erasure correction capability simultaneously and obtaingood erasure correction capability even when the coding rate is changedduring erasure correction.

An LDPC-CC of a time varying period of 3 has been described so far as anexample, but also for an LDPC-CC of a time varying period of 3g (g=1, 2,3, 4, . . . ) having good characteristics described in Embodiment 2(that is, LDPC-CC whose time varying period is a multiple of 3), thecoding rate can be made variable while maintaining high error correctioncapability by satisfying above [method #3-1] to [method #3-3] in thesame way as for an LDPC-CC of a time varying period of 3.

The present invention is not limited to the above-described embodiments,and can be implemented with various changes. For example, although caseshave been mainly described above with embodiments where the presentinvention is implemented with an encoder and transmitting apparatus, thepresent invention is not limited to this, and is applicable to cases ofimplementation by means of a power line communication apparatus.

It is also possible to implement the encoding method and transmittingmethod as software. For example, provision may be made for a programthat executes the above-described encoding method and communicationmethod to be stored in ROM (Read Only Memory) beforehand, and for thisprogram to be run by a CPU (Central Processing Unit).

Provision may also be made for a program that executes theabove-described encoding method and transmitting method to be stored ina computer-readable storage medium, for the program stored in thestorage medium to be recorded in RAM (Random Access Memory) of acomputer, and for the computer to be operated in accordance with thatprogram.

It goes without saying that the present invention is not limited towireless communication, and is also useful in power line communication(PLC), visible light communication, and optical communication.

Embodiment 5

An LDPC-CC having high error correction capability has been described inEmbodiment 2. The present embodiment will complementarily describe anLDPC-CC of a time varying period of 3 having high error correctioncapability. In the case of an LDPC-CC of a time varying period of 3,when a regular LDPC code is generated, a code of high error correctioncapability can be created.

Parity check polynomials of an LDPC-CC of a time varying period of 3will be presented again. Suppose the relationship between parity checkpolynomials and a parity check matrix is the same as that described inEmbodiment 2 and Embodiment 5.

When coding rate is 1/2:[28](D ^(a1) +D ^(a2) +D ^(a3))X(D)+(D ^(b1) +D ^(b2) +D^(b3))P(D)=0  (Equation 28-1)(D ^(A1) +D ^(A2) +D ^(A3))X(D)+(D ^(B1) +D ^(B2) +D^(B3))P(D)=0  (Equation 28-2)(D ^(a1) +D ^(a2) +D ^(a3))X(D)+(D ^(B1) +D ^(B2) +D^(B3))P(D)=0  (Equation 28-3)

When coding rate is (n−1)/n:[29](D ^(a1,1) +D ^(a1,2) +D ^(a1,3))X ₁(D)+(D ^(a2,1) +D ^(a2,2) +D^(a2,3))X ₂(D)= . . . +(D ^(an−1,1) +D ^(an−1,2) +D ^(an−1,3))X_(n−1)(D)+(D ^(b1) +D ^(b2) +D ^(b3))P(D)=0  (Equation 29-1)(D ^(A1,1) +D ^(A1,2) +D ^(A1,3))X ₁(D)+(D ^(A2,1) +D ^(A2,2) +D^(A2,3))X ₂(D)= . . . +(D ^(An-1,1) +D ^(An-1,2) +D ^(An-1,3))X_(n−1)(D)+(D ^(B1) +D ^(B2) +D ^(B3))P(D)=0  (Equation 29-2)(D ^(a1,1) +D ^(a1,2) +D ^(a1,3))X ₁(D)+(D ^(a2,1) +D ^(a2,2) +D^(a2,3))X ₂(D)= . . . +(D ^(an−1,1) +D ^(an−1,2) +D ^(an−1,3))X_(n−1)(D)+(D ^(b1) +D ^(b2) +D ^(b3))P(D)=0  (Equation 29-3)

Here, the parity check matrix becomes a full rank and it is assumed thatthe following condition holds true so that parity bits may besequentially and easily calculated.b3=0, that is, D ^(b3)=1B3=0, that is, D ^(B3)=1β3=0, that is, Dβ ³=1

Furthermore, the following conditions may be preferably given to makethe relationship between information and parity part easy to understand.a1,3=0, that is, D ^(ai,3)=1(i=1,2, . . . ,n−1)Ai,3=0, that is, D ^(Ai,3)=1(i=1,2, . . . ,n−1)αi,3=0, that is, Dα ^(i,3)1(i=1,2, . . . ,n−1)

where, ai,3%3=0, Ai,3%3=0, αi,3%3=0 may also be possible.

To generate a regular LDPC code having high error correction capabilityby reducing the number of loops 6 (cycle length of 6) in a Tanner graphat this time, the following condition must be satisfied.

That is, when attention is focused on coefficients of informationXk(k=1, 2, . . . , n−1), any of #Xk1 to #Xk14 must be satisfied.#Xk1:(ak,1%3,ak,2%3)=[0,1],(Ak,1%3,Ak,2%3)=[0,1],(αk,1%3,αk,2%3)=[0,1]#Xk2:(ak,1%3,ak,2%3)[0,1],(Ak,1%3,Ak,2%3)[0,2],(αk,1%3,αk,2%3)=[1,2]#Xk3:(ak,1%3,ak,2%3)=[0,1],(Ak,1%3,Ak,2%3)[1,2],(αk,1%3,αk,2%3)=[1,1]#Xk4:(ak,1%3,ak,2%3)=[0,2],(Ak,1%3,Ak,2%3)=[1,2],(αk,1%3,αk,2%3)[0,1]#Xk5:(ak,1%3,ak,2%3)=[0,2],(Ak,1%3, Ak,2%3)=[0,2],(αk,1%3,αk,2%3)=[0,2]#Xk6:(ak,1%3,ak,2%3)=[0,2],(Ak,1%3,Ak,2%3)=[2,2](αk,1%3,ak,2%3)=[1,2]#Xk7:(ak,1%3,ak,2%3)=[1,1],(Ak,1%3,Ak,2%3)=[0,1],(αk,1%3,αk,2%3)=[1,2]#Xk8:(ak,1%3,ak,2%3)=[1,1](Ak,1%3,Ak,2%3)=[1,1],(αk,1%3,αk,2%3)=[1,1]#Xk9:(ak,1%3,ak,2%3)[1,2],(Ak,1%3,Ak,2%3)=[0,1],(αk,1%3,αk,2%3)=[0,2]#Xk10:(ak,1%3,ak,2%3)=[1,2],(Ak,1%3,Ak,2%3)=[0,2],(αk,1%3,αk,2%3)=[2,2]#Xk11:(ak,1%3,ak,2%3)=[1,2],(Ak,1%3,Ak,2%3)=[1,1],(αk,1%3,αk,2%3)=[0,1]#Xk12:(ak,1%3,ak,2%3)=[1,2],(Ak,1%3,Ak,2%3)=[1,2],(αk,1%3,αk,2%3)=a[1,2]#Xk13:(ak,1%3,ak,2%3)=[2,2],(Ak,1%3,Ak,2%3)=[1,2],(αk,1%3,αk,2%3)=[0,2]#Xk14:(ak,1%3,ak,2%3)=[2,2],(Ak,1%3,Ak,2%3)=[2,2],(αk,1%3,αk,2%3)=[2,2]

When a=b in the above description, (x, y)=[a, b] represents x=y=a(=b)and when a≠b, (x, y)=[a, b] represents x=a, y=b or x=b, y=a (the sameshall apply hereinafter).

Similarly, when attention is focused on coefficients of parity part, anyof #P1 to #P14 must be satisfied. #P1:(b1%3,b2%3) [0,1],(B1%3,B2%3)=[0,1], (β1%3β2%3)=[0,1]

#P2:(b1%3,b2%3)=[0,1], (B1%3,B2%3)=[0,2], (β1%3,β2%3)=[1,2]

#P3:(b1%3,b2%3)=[0,1], (B1%3,B2%3)=[1,2], (β1%3,β2%3)=[1,1]

#P4:(b1%3,b2%3)=[0,2], (B1%3,B2%3)=[1,2], (β1%3,β2%3)=[0,1]

#P5:(b1%3,b2%3)=[0,2], (B1%3,B2%3)=[0,2], (β1%3,β2%3)=[0,2]

#P6:(b1%3,b2%3)=[0,2], (B1%3,B2%3)=[2,2], (β1%3,β2%3)=[1,2]

#P7:(b1%3,b2%3)=[1,1], (B1%3,B2%3)=[0,1], (β1%3,β2%3)=[1,2]

#P8:(b1%3,b2%3)=[1,1], (B1%3,B2%3)=[1,1], (β1%3,β2%3)=[1,1]

#P9:(b1%3,b2%3)=[1,1], (B1%3,B2%3)=[1,1], (β1%3,β2%3)=[0,2]

#P10:(b1%3,b2%3)=[1,2], (B1%3,B2%3)=[0,1], (β1%3,β2%3)=[0,2]

#P11:(b1%3,b2%3)=[1,2], (B1%3,B2%3)=[1,1], (β1%3,β2%3)=[0,1]

#P13:(b1%3,b2%3)=[1,2], (B1%3,B2%3)=[1,2], (β1%3,β2%3)=[0,2]

#P14:(b1%3,b2%3)=[2,2], (B1%3,B2%3)=[2,2], (β1%3,β2%3)=[2,2]

The LDPC-CC having good characteristics described in Embodiment 2 is anLDPC-CC that satisfies the conditions of #Xk12 and #P12 of the aboveconditions.

The following is an example of parity check polynomials of an LDPC-CC ofa time varying period of 3 that satisfies #Xk12 of above #Xk1 to #Xk14and that satisfies the condition of #P12 of #P1 to #P14.

Coding Rate R=1/2:[30]A _(X1,1)(D)X ₁(D)+B ₁(D)P(D)=(D ²⁸⁶ +D ¹⁶⁴+1)X ₁(D)+(D ⁹² +D⁷+1P(D)=0  (Equation 30-1)A _(X1,2)(D)X ₁(D)+B ₂(D)P(D)=(D ³⁷⁰ +D ³¹⁷+1)X ₁(D)+(D ⁹⁵ +D²²+1P(D)=0  (Equation 30-2)A _(X1,3)(D)X ₁(D)+B ₃(D)P(D)=(D ³⁴⁶ +D ⁸⁶+1)X ₁(D)+(D ⁸⁸ +D²⁶+1P(D)=0  (Equation 30-3)

Coding Rate R=2/3:[31]A _(X1,1)(D)X ₁(D)+A _(X2,1)(D)X ₂(D)+B ₁(D)P(D)=(D ²⁸⁶ +D ¹⁶⁴+1)X₁(D)+(D ³⁸⁵ +D ²⁴²+1)X ₂(D)+(D ⁹² +D ⁷)P(D)=0  (Equation 31-1)A _(X1,2)(D)X ₁(D)+A _(X2,2)(D)X ₂(D)+B ₂(D)P(D)=(D ³⁷⁰ +D ³¹⁷+1)X₁(D)+(D ¹²⁵ +D ¹⁰³+1)X ₂(D)+(D ⁹⁵ +D ²²)P(D)=0  (Equation 31-2)A _(X1,3)(D)X ₁(D)+A _(X2,3)(D)X ₂(D)+B ₃(D)P(D)=(D ³⁴⁶ +D ⁸⁶+1)X₁(D)+(D ³¹⁹ +D ²⁹⁰+1)X ₂(D)+(D ⁸⁸ +D ²⁶)P(D)=0  (Equation 31-2)Coding Rate R=3/4:[32]A _(X1,1)(D)X ₁(D)+A _(X2,1)(D)X ₂(D)+A _(X3,1)(D)X ₃(D)+B ₁(D)P(D)=(D²⁸⁶ +D ¹⁶⁴+1)X ₁(D)+(D ³⁸⁵ +D ²⁴²+1)X ₂(D)+(D ³⁴³ +D ²⁸⁴)X ₃(D)+(D ⁹² +D⁷+1)P(D)=0  (Equation 32-1)A _(X1,2)(D)X ₁(D)+A _(X2,2)(D)X ₂(D)+A _(X3,2)(D)X ₃(D)+B ₂(D)P(D)=(D³⁷⁰ +D ³¹⁷+1)X ₁(D)+(D ¹²⁵ +D ¹⁰³+1)X ₂(D)+(D ²⁵⁹ +D ¹⁴)X ₃(D)+(D ⁹⁵ +D²²+1)P(D)=0  (Equation 32-2)A _(X1,3)(D)X ₁(D)+A _(X2,3)(D)X ₂(D)+A _(X3,3)(D)X ₃(D)+B ₃(D)P(D)=(D³⁴⁶ +D ⁸⁶+1)X ₁(D)+(D ³¹⁹ +D ¹⁹⁰+1)X ₂(D)+(D ¹⁴⁵ +D ¹¹+1)X ₃(D)+(D ⁸⁸ +D²⁶+1)P(D)=0  (Equation 32-3)

Coding Rate R=4/5:[33]A _(X1,1)(D)X ₁(D)+A _(X2,1)(D)X ₂(D)+A _(X3,1)(D)X ₃(D)+A _(X4,1)(D)X₄(D)+B ₁(D)P(D)=(D ²⁸⁶ +D ¹⁶⁴+1)X ₁(D)+(D ³⁸⁵ +D ²⁴²+1)X ₂(D)+(D ³⁴³ +D²⁸⁴+1)X ₃(D)+(D ²⁸³ +D ⁶⁸+1)X ₄(D)+(D ⁹² +D ⁷+1)P(D)=0  (Equation 33-1)A _(X1,2)(D)X ₁(D)+A _(X2,2)(D)X ₂(D)+A _(X3,2)(D)X ₃(D)+A _(X4,2)(D)X₄(D)+B ₂(D)P(D)=(D ³⁷⁰ +D ³¹⁷+1)X ₁(D)+(D ¹²⁵ +D ¹⁰³+1)X ₂(D)+(D ²⁵⁹ +D¹⁴+1)X ₃(D)+(D ²⁵⁶ +D ¹⁸⁸+1)X ₄(D)+(D ⁹⁵ +D ²²+1)P(D)=0  (Equation 33-2)A _(X1,3)(D)X ₁(D)+A _(X2,3)(D)X ₂(D)+A _(X3,3)(D)X ₃(D)+A _(X4,3)(D)X₄(D)+B ₃(D)P(D)=(D ³⁴⁶ +D ⁸⁶+1)X ₁(D)+(D ³¹⁹ +D ²⁹⁰+1)X ₂(D)+(D ¹⁴⁵ +D¹¹+1)X ₃(D)+(D ²⁸⁷ +D ⁷³+1)X ₄(D)+(D ⁸⁸ +D ²⁶+1)P(D)=0  (Equation 33-3)

The above LDPC-CC parity check polynomials have a characteristic ofenabling the shared use of encoder circuits and the shared use ofdecoders.

Another example of LDPC-C parity check polynomials of a time varyingperiod of 3 is shown below.

Coding Rate R=1/2:[34]A _(X1,1)(D)X ₁(D)+B ₁(D)P(D)=(D ²¹⁴ +D ¹⁸⁵+1)X ₁(D)+(D ²¹⁵ +D¹⁴⁵+1)P(D)=0  (Equation 34-1)A _(X1,2)(D)X ₁(D)+B ₂(D)P(D)=(D ¹⁶⁰ +D ⁶²+1)X ₁(D)+(D ²⁹⁶ +D¹²⁷+1)P(D)=0  (Equation 34-2)A _(X1,3)(D)X ₁(D)+B ₃(D)P(D)=(D ¹⁹⁶ +D ¹⁴³+1)X ₁(D)+(D ²¹¹ +D¹¹⁹+1)P(D)=0  (Equation 34-3)

Coding Rate R=2/3:[35]A _(X1,1)(D)X ₁(D)A _(X2,1)(D)X ₂(D)+B ₁(D)P(D)=(D ²¹⁴ +D ¹⁸⁵+1)X₁(D)+(D ¹⁹⁴ +D ⁶⁷+1)X ₂(D)+(D ²¹⁵ +D ¹⁴⁵+1)P(D)=0  (Equation 35-1)A _(X1,2)(D)X ₁(D)A _(X2,2)(D)X ₂(D)+B ₂(D)P(D)=(D ¹⁶⁰ +D ⁶²+1)X ₁(D)+(D²²⁶ +D ²⁰⁹+1)X ₂(D)+(D ²⁰⁶ +D ¹²⁷+1)P(D)=0  (Equation 35-2)A _(X1,3)(D)X ₁(D)A _(X2,3)(D)X ₂(D)+B ₃(D)P(D)=(D ¹⁹⁶ +D ¹⁴³+1)X₁(D)+(D ¹¹⁵ +D ¹⁰⁴+1)X ₂(D)+(D ²¹¹ +D ¹¹⁹+1)P(D)=0  (Equation 35-3)

Coding Rate R=3/4:[36]A _(X1,1)(D)X ₁(D)A _(X2,1)(D)X ₂(D)+A _(X3,1)(D)X ₃(D)+B ₁(D)P(D)=(D²¹⁴ +D ¹⁸⁵+1)X ₁(D)+(D ¹⁹⁴ +D ⁶⁷+1)X ₂(D)+(D ¹⁹⁶ +D ⁶⁸+1)X ₃(D)+(D ²¹⁵+D ¹⁴⁵+1)P(D)=0  (Equation 36-1)A _(X1,2)(D)X ₁(D)A _(X2,2)(D)X ₂(D)+A _(X3,2)(D)X ₃(D)+B ₂(D)P(D)=(D¹⁶⁰ +D ⁶²+1)X ₁(D)+(D ²²⁶ +D ²⁰⁹+1)X ₂(D)+(D ⁹⁸ +D ³⁷+1)X ₃(D)+(D ²⁰⁶ +D¹²⁷+1)P(D)=0  (Equation 36-2)A _(X1,3)(D)X ₁(D)A _(X2,3)(D)X ₂(D)+A _(X3,3)(D)X ₃(D)+B ₃(D)P(D)=(D¹⁹⁶ +D ¹⁴³+1)X ₁(D)+(D ¹¹⁵ +D ¹⁰⁴+1)X ₂(D)+(D ¹⁷⁶ +D ¹³⁶+1)X ₃(D)+(D ²¹¹+D ¹¹⁹+1)P(D)=0  (Equation 36-3)

Coding Rate R=4/5:[37]A _(X1,1)(D)X ₁(D)A _(X2,1)(D)X ₂(D)+A _(X3,1)(D)X ₃(D)+A _(X4,1)(D)X₄(D)++B ₁(D)P(D)=(D ²¹⁴ +D ¹⁸⁵+1)X ₁(D)+(D ¹⁹⁴ +D ⁶⁷+1)X ₂(D)+(D ¹⁹⁶ +D⁶⁸+1)X ₃(D)+(D ²¹⁷ +D ¹²²+1)X ₄(D)+(D ²¹⁵ +D ¹⁴⁵+1)P(D)=0  (Equation37-1)A _(X1,2)(D)X ₁(D)A _(X2,2)(D)X ₂(D)+A _(X3,2)(D)X ₃(D)+A _(X4,2)(D)X₄(D)++B ₂(D)P(D)=(D ¹⁶⁰ +D ⁶²+1)X ₁(D)+(D ²²⁶ +D ²⁰⁹+1)X ₂(D)+(D ⁹⁸ +D³⁷+1)X ₃(D)+(D ⁷¹ +D ³⁴+1)X ₄(D)+(D ²⁰⁶ +D ¹²⁷+1)P(D)=0  (Equation 37-2)A _(X1,3)(D)X ₁(D)A _(X2,3)(D)X ₂(D)+A _(X3,3)(D)X ₃(D)+A _(X4,3)(D)X₄(D)++B ₃(D)P(D)=(D ¹⁹⁶ +D ¹⁴³+1)X ₁(D)+(D ¹¹⁵ +D ¹⁰⁴+1)X ₂(D)+(D ¹⁷⁶ +D¹³⁶+1)X ₃(D)+(D ²¹² +D ¹⁸⁷+1)X ₄(D)+(D ²¹¹ +D ¹¹⁹+1)P(D)=0  (Equation37-3)

The above example is an example of LDPC-CC parity check polynomials of atime varying period of 3 that satisfy #Xk12 of above #Xk1 to #Xk14 andsatisfies the condition of #P12 of #P1 to #P14, but satisfyingconditions other than #Xk12 or #P12 can also create an LDPC-CC of a timevarying period of 3 having good error correction capability. Detailsthereof will be described in Embodiment 6.

Use of an LDPC-CC relating to the present invention requires terminationor tail-biting to secure reliability in decoding of information bits. Acase where termination is performed (referred to as“information-zero-termination” or simply referred to as“zero-termination”) and the tail-biting method will be described indetail below. All the embodiments of the present invention can beimplemented when either termination or tail-biting is performed.

FIG. 33 is a diagram illustrating “Information-zero-termination” in anLDPC-CC of a coding rate of (n−1)/n. Suppose information bits X₁, X₂, .. . , X_(n−1), and parity bit P at point in time i (i=0, 1, 2, 3, . . ., s) are X_(1,i), X_(2,i), . . . , X_(n−1,i), and parity bit P_(i)respectively. As shown in FIG. 33, suppose X_(n−1,s) is the final bit ofinformation to be transmitted.

When the encoder performs encoding only up to point in time s and thetransmitting apparatus on the encoding side performs transmission to thereceiving apparatus on the decoding side only up to P_(s), the receivingquality of information bits on the decoder significantly deteriorates.To solve this problem, encoding is performed assuming information bitsfrom final information bit X_(n−1,s) onward (referred to as “virtualinformation bit”) to be 0's and parity bits (3303) are generated.

To be more specific, as shown in FIG. 33, the encoder performs encodingassuming X_(1,k), X_(2,k), . . . , X_(n−1,k) (k=t1, t2, . . . , tm) tobe 0's and obtains P_(t1), P_(t2), . . . , P_(tm). The transmittingapparatus on the encoding side transmits X_(1,s), X_(2,s), . . . ,X_(n−1,s), P₅ at point in time s and then transmits P_(t1), P_(t2), . .. , P_(tm). The decoder performs decoding taking advantage of knowingthat virtual information bits from point in time s onward are 0's.

Next, the tail-biting method will be described. A general equation of aparity check matrix when performing tail-biting of a time-varyingLDPC-CC is represented as shown below.

$\begin{matrix}\lbrack 38\rbrack & \; \\{H^{T} = \begin{bmatrix}{H_{0}^{T}(0)} & {H_{1}^{T}(1)} & \ldots & {H_{Ms}^{T}\left( M_{s} \right)} & 0 & \; & \ldots & \; & 0 \\0 & {H_{0}^{T}(1)} & \ldots & {H_{{Ms} - 1}^{T}\left( M_{s} \right)} & {H_{Ms}^{T}\left( {M_{s} + 1} \right)} & 0 & \ldots & \; & 0 \\\; & \ddots & \; & \; & \ddots & \; & \; & \ddots & \; \\{H_{Ms}^{T}(N)} & 0 & \; & \ldots & \; & \; & \; & {H_{{Ms} - 2}^{T}\left( {N - 2} \right)} & {H_{{Ms} - 2}^{T}\left( {N - 1} \right)} \\{H_{{Ms} - 1}^{T}(N)} & {H_{Ms}^{T}\left( {N + 1} \right)} & 0 & \; & \; & \; & \; & {H_{{Ms} - 3}^{T}\left( {N - 2} \right)} & {H_{{Ms} - 2}^{T}\left( {N - 1} \right)} \\\vdots & \; & \; & \; & \ldots & \; & \; & \vdots & \vdots \\{H_{1}^{T}(N)} & {H_{2}^{T}\left( {N + 1} \right)} & \ldots & 0 & \; & \ldots & \; & 0 & {H_{0}^{T}\left( {N - 1} \right)}\end{bmatrix}} & \left( {{Equation}\mspace{14mu} 38} \right)\end{matrix}$

In the above equation, H represents a parity check matrix and H^(T)represents a syndrome former. Furthermore, H^(T) _(i)(t)(i=0, 1, . . . ,M_(s)) is a sub-matrix of c×(c−b) and M_(s) represents a memory size.Encoding is performed and a parity part is found based on the aboveparity check matrix. Thus, in general, when tail-biting is performed, afixed block size (coding unit) is determined.

Embodiment 6

The present embodiment will describe important items about the design ofthe good LDPC-CC of a time varying period of 3 described in Embodiment3.

As for a convolutional code, studies have been so far carried out onViterbi decoding and sequential decoding of a code based on a minimumfree distance (see Non-Patent Literature 10 to Non-Patent Literature13). In particular, when attention is focused on a time-varyingconvolutional code (see Non-Patent Literature 14 and Non-PatentLiterature 15), these documents show that there are codes excellingtime-invariant convolutional codes in minimum free distances amongperiodic time-varying convolutional codes (see Non-Patent Literature15).

On the other hand, an LDPC (Low-Density Parity-Check) code (seeNon-Patent Literature 4 and Non-Patent Literature 19) is attractingattention in recent years from the standpoint that it providescharacteristics close to a Shannon limit and that it can realizedecoding using a simple belief propagation algorithm such as BP (BeliefPropagation) decoding (see Non-Patent Literature 16 and Non-PatentLiterature 17). Many studies carried out so far are concerned with LDPCblock codes (LDPC-BC) and studies on random LDPC codes (see Non-PatentLiterature 2), algebraically configured array LDPC codes (see Non-PatentLiterature 18), QC (Quasi-Cyclic)-LDPC codes (see Non-Patent Literature19 to Non-Patent Literature 21) or the like are in progress.

On the other hand, Non-Patent Literature 3 proposes a concept of LDPCconvolutional codes (LDPC-CC). An LDPC-CC encoder can be constitutedusing simple shift registers, a parity check matrix is defined on thebasis of sub-matrices and BP decoding is performed using the paritycheck matrices. The concept of time variation is also introduced toLDPC-CCs in much the same way as convolutional codes (see Non-PatentLiterature 3). Moreover, many literatures disclose methods of creatingconvolutional codes and LDPC-CCs from block codes (see Non-PatentLiterature 22 to Non-Patent Literature 25).

Non-Patent Literature 26 and Non-Patent Literature 27 are discussing adesign method for an LDPC-CC (TV3-LDPC-CC) of a time varying period of3.

Thus, a design method for a TV3-LDPC-CC will be discussed below. NPL 26and Non-Patent Literature 27 evaluate the number of short cycle lengths(CL: cycle of length) in a Tanner graph and have confirmed that thereare only a small number of CL4's (CL of 4). Therefore, aiming at areduction in the number of CL6's (CL of 6), one condition for CL6 tooccur in a TV3-LDPC-CC will be described below. Then, a method ofgenerating a TV3-LDPC-CC which becomes a regular LDPC code withoutsatisfying the generating condition will be described.

<About LDPC-CC> (See Non-Patent Literature 20)

An LDPC-CC is a code defined by a low-density parity check matrix in thesame way as an LDPC-BC and can be defined by a time-varying parity checkmatrix of infinite length, but can actually be thought of with aperiodically time-varying parity check matrix. Assuming a parity checkmatrix as H, an LDPC-CC will be described using syndrome former H^(T).

H^(T) of the LDPC-CC of a coding rate of R-b/c (b<c) can be representedas equation 39.

$\begin{matrix}\lbrack 39\rbrack & \; \\{H^{T} = \begin{bmatrix}\ddots & \vdots & \vdots & \ddots & \; & \; & \; & \; & \; \\\; & {H_{0}^{T}\left( {t - M_{s}} \right)} & {H_{1}^{T}\left( {t - M_{s} + 1} \right)} & \ldots & {H_{Ms}^{T}(t)} & \; & \; & \; & \; \\\; & \; & {H_{0}^{T}\left( {t - M_{s} + 1} \right)} & \ldots & {H_{{Ms} - 1}^{T}(t)} & {H_{Ms}^{T}\left( {t + 1} \right)} & \; & \; & \; \\\; & \; & \; & \ddots & \vdots & \vdots & \ddots & \; & \; \\\; & \; & \; & \; & {H_{0}^{T}(t)} & {H_{1}^{T}\left( {t + 1} \right)} & \ldots & {H_{Ms}^{T}\left( {t + M_{s}} \right)} & \; \\\; & \; & \; & \; & \; & \ddots & \vdots & \vdots & \ddots\end{bmatrix}} & \left( {{Equation}\mspace{14mu} 39} \right)\end{matrix}$

In equation 39, H^(T) _(i)(t) (i=0,1, . . . , m_(s)) is a sub-matrix ofa c×(c−b) period. When the period is assumed as T_(s), H^(T)_(i)(t)=H^(T) _(i)(t+T_(s)) holds true for ^(∀)I and ^(∀)t. Furthermore,M_(s) represents a memory size.

The LDPC-CC defined by equation 39 is a time-varying convolutional codeand this code is called “time-varying LDPC-CC” (see Non-PatentLiterature 3).

Decoding is generally performed through BP decoding using parity checkmatrix H. When an encoded sequence vector is assumed to be u, thefollowing relational equation holds true.[40]Hu=0  (Equation 40)

By performing BP decoding, an information sequence is obtained from therelational equation of equation 40.

<About LDPC-CC Based on Parity Check Polynomial>

Consider a systematic convolutional code of a coding rate of R=1/2 andgenerator matrix G=[1 G₁(D)/G₀(D)]. In this case, G₁ represents afeedforward polynomial and G₀ represents a feedback polynomial. Assuminga polynomial representation of an information sequence is X(D) and apolynomial representation of a parity sequence is P(D), the parity checkpolynomial can be represented as follows.[41]G ₁(D)X(D)+G ₀(D)P(D)=0  (Equation 41)

Here, consider a parity check polynomial of equation 42 that satisfiesequation 41.[42](D ^(a) ¹ +D ^(a) ² + . . . +D ^(a) ¹ +1)X(D)+(D ^(b) ¹ +D ^(b) ² + . .. +D ^(b) ¹ +1)P(D)=0  (Equation 42)

In equation 42, a_(p) and b_(q) are integers equal to or greater than 1(p=1, 2 . . . , r; q=1, 2 . . . , s) and a D⁰ term is present in X(D)and P(D). The code defined by the parity check matrix based on theparity check polynomial of equation 42 becomes a time-invariant LDPC-CC.

M different parity check polynomials based on equation 42 are provided(where m is an integer equal to or greater than 2). The parity checkpolynomial is represented as shown below.[43]A _(i)(D)X(D)+B _(i)(D)P(D)=0  (Equation 43)

In this case, i=0, 1, . . . , m−1. Data and parity part at point in timej are represented as X_(j) and P_(j), and assume u_(j)=(X_(j), P_(j)).Then, a parity check polynomial of equation 44 also holds true.[44]A _(k)(D)X(D)+B _(k)(D)P(D)=0(k=j mod m)  (Equation 44)

In this case, parity part P_(j) at point in time j can be obtained fromequation 44. A code defined by the parity check matrix generated basedon the parity check polynomial of equation 44 becomes a time-varyingLDPC-CC. In this case, since the D⁰ term is present in P(D) and b_(j) isan integer equal to or greater than 1, the time-invariant LDPC-CCdefined by the parity check polynomial of equation 42 and thetime-varying LDPC-CC defined by the parity check polynomial of equation44 have a characteristic of enabling a parity part to be easily foundsequentially by means of a register and exclusive OR.

The decoding section creates parity check matrix H for a time-invariantLDPC-CC in accordance with equation 42 and for a time-varying LDPC-CC inaccordance with equation 44, performs BP decoding from the relationalequation of equation 40 using a representation encoded sequence u=(u₀,u₁, . . . , u_(j), . . . )^(T), and obtains a data sequence.

Next, consider a time-invariant LDPC-CC and time-varying LDPC-CC of acoding rate of (n−1)/n. Suppose information sequence X₁, X₂, . . . ,X_(n−1) and parity part P at point in time j are represented by X_(2,j),. . . , X_(n−1,j) and P_(j) respectively, and consider u_(j)=(X_(1,j),X_(2,j), . . . , X_(n−1,j), P_(j)). Assuming a polynomial representationof information sequence X₁, X₂, . . . , X_(n−1) as X₁(D), X₂(D), . . . ,X_(n−1)(D), the parity check polynomial is represented as shown below.[45](D ^(a) ^(1,1) +D ^(a) ^(1,2) + . . . +D ^(a) ^(1,3) +1)X ₁(D)+(D ^(a)^(2,1) +D ^(a) ^(2,2) + . . . D ^(a) ^(2,3) +1)X ₂(D)+ . . . +(D ^(a)^(n-1,1) +D ^(a) ^(n-1,2) + . . . +D ^(a) ^(n-1, rn-1) +1)X _(n−1)(D)+(D^(b) ¹ +D ^(b) ² + . . . +D ^(b) ³ +1)P(D)=0  (Equation 45)

In equation 45, a_(p,1), is an integer equal to or greater than 1 (p=1,2, . . . , n−1; i=1, 2, . . . , r_(p)), satisfies a_(p,y)≠a_(p,z) andsatisfies (^(∀)(y,z)|y,z=1, 2, . . . , r_(p), y≠z) andb_(y)≠b_(z)(^(∀)(y,z)|y,z=1, 2, . . . , ε, y≠z). M different paritycheck polynomials based on equation 45 are provided (where m is aninteger equal to or greater than 2). The parity check polynomial isrepresented as shown below.[46]A _(X1,i)(D)X ₁(D)=A _(X2,i)(D)X ₂(D)+ . . . +A _(Xn-1,i)(D)X_(n−1)(D)+D _(i)(D)P(D)=0  (Equation 46)

In this case, i=0, 1, . . . , m−1. Then, suppose equation 47 holds truefor X_(1,j), X_(2,j), . . . , X_(n−1,j) and P_(j) which are informationsequence X₁, X₂, . . . , X_(n−1) and parity part P at point in time j.[47]A _(X1,k)(D)X ₁(D)+A _(X2,k)(D)X ₂(D)+ . . . +A _(Xn−1,k)(D)X_(n−1)(D)+B _(k)(D)P(D)=0(k=j mod m)  (Equation 47)

In this case, the codes based on equation 45 and equation 47 are thetime-invariant LDPC-CC and time-varying LDPC-CC of a coding rate of(n−1)/n respectively.

Non-Patent Literature 27 describes that when constraint lengths areapproximately equal, a TV3-LDPC-CC can obtain better error correctioncapability than an LDPC-CC of a time varying period of 2. Thus, byfocusing attention on the TV3-LDPC-CC, the design method of the regularTV3-LDPC-CC will be described in detail.

A parity check polynomial that satisfies #q-th 0 of the TV3-LDPC-CC of acoding rate of (n−1)/n is provided as shown below (q=0, 1, 2).[48](D ^(a) ^(#q,1,1) +D ^(a) ^(#q,1,2) + . . . +D ^(a#q,1,r1))X ₁(D)+(D^(a) ^(#q,2,1) +D ^(a) ^(#q,2,2) + . . . D ^(a) ^(#q,2,r2) )X ₂(D)+ . .. +(D ^(a) ^(#q,n-1,1) +D ^(a) ^(#q,n-1,2) + . . . +D ^(a)^(#q,n-1,rn-1) )X _(n−1)(D)+(D ^(b) ^(#q,1) +D ^(b) ^(#q,2) + . . . +D^(b) ^(#q,3) )P(D)=0  (Equation 48)

In equation 48, a_(#q,p,i) is an integer equal to or greater than 1(p=1, 2, . . . , n−1; i=1, 2, . . . , r_(p)), satisfiesa_(#q,p,y)≠a_(#q,p,z) and satisfies ((y,z)|y,z=1, 2, . . . , r_(p), y≠z)and b_(#q,y)≠b_(#q,z) (^(∀)(y,z)|y,z=1, 2, . . . , ε, y≠z).

In this case, there are features as shown below.

Feature 1:

There are relationships as shown below between the D^(a#)α·^(p,i)X_(p)(D) term of parity check polynomial #α, D^(a#)β·^(p,j)X_(p)(D) term ofparity check polynomial #β (α,β=0, 1, 2(α≠β); p=1, 2, . . . , n−1;i,j=1, 2, . . . , r_(p)), and between the D^(b#)α·^(i)P(D) term ofparity check polynomial #α and D^(b#)β·^(j)P(D) term of parity checkpolynomial #β (α,β=0, 1, 2(α≠β); i,j=1, 2, . . . , r_(p)).

<1> when β=α:

When {(a_(#)α_(p,i) mod 3,a_(#)β_(p,j) mod 3)=(0,0)∪(1,1)∪(2,2)}∩{i≠j}holds true, variable node $1 is present which forms edges 2003 of both acheck node 2001 corresponding to parity check polynomial #α and a checknode 2002 corresponding to parity check polynomial #β as shown in FIG.34. Here, since β≠α, a condition of i≠j needs to be added. When{(b_(#)α,_(i) mod 3,b_(#)β,_(j) mod 3)=(0,0)∪(1,1)∪(2,2}∩{i·j} holdstrue, variable node $1 is present which forms edges 2003 of both a checknode 2001 corresponding to parity check polynomial #a and a check node2002 corresponding to parity check polynomial #3 as shown in FIG. 34.

<2> when β=(α+1) Mod 3:

When (a_(#)α,_(p,i) mod 3,α_(#)β,_(p,j) mod 3)=(0,1)∪(1,2)∪(2,0) holdstrue, variable node $1 is present which forms edges of both a check nodecorresponding to parity check polynomial #α and a check nodecorresponding to parity check polynomial #β as shown in FIG. 34. When(b_(#)α_(,i) mod 3,b_(#)β_(ij) mod 3)=(0,1)∪(1,2)∪(2,0) holds true,variable node $1 is present which forms edges of both a check nodecorresponding to parity check polynomial #α and a check nodecorresponding to parity check polynomial #β as shown in FIG. 34.

<3> when β=(α+2) Mod 3:

When (a_(#)α_(,p,i) mod 3,a_(#)β_(,p,j) mod 3)=(0,2)∪(1,0)∪(2,1) holdstrue, variable node $1 is present which forms edges of both a check nodecorresponding to parity check polynomial #α and a check nodecorresponding to parity check polynomial #β as shown in FIG. 34. When(b_(#)α_(ii) mod 3,b_(#)β_(ij) mod 3)=(0,2)∪(1,0)∪(2,1) holds true,variable node $1 is present which forms edges of both a check nodecorresponding to parity check polynomial #α and a check nodecorresponding to parity check polynomial #β as shown in FIG. 34.

The following theorem relating to cycle length 6 (CL6: cycle length of6) of a TV3-LDPC-CC holds true.

Theorem 1:

The following two conditions are provided for parity check polynomialsthat satisfy 0's of a TV3-LDPC-CC.

P and q that satisfy C#1.1:(a_(#q,p,i) mod 3,a_(#q,p,j) mod 3,a_(#q,p,k)mod 3)=(0, 0, 0)∪(1, 1, 1)∪(2, 2, 2) are present, where i≠j, i≠k and j≠kare assumed.

P and q that satisfy C#1.2:(b_(#q,i) mod 3,b_(#q,j) mod 3,b_(#q,k) mod3)=(0, 0, 0)∪(1, 1, 1)∪(2, 2, 2, where i≠j, i≠k and j≠k are assumed.

When C#1.1 or C#1.2 is satisfied, at least one CL6 is present.

Proof:

If it is possible to prove that at least one CL6 is present when p=1,q=0, and (a_(#0,1,i) mod 3, a_(#0,1,i) mod 3, a_(#0,l,k) mod 3)=(0, 0,0)∪(1, 1, 1)∪(2, 2, 2), it is possible to prove that at least one CL6 ispresent also for X₂(D), . . . , X_(n−1)(D), P(D) by substituting X₂(D),. . . , X_(n−1)(D),P(D) for X₁(D), if C#1.1 and C#1.2 hold true whenq=0.

Furthermore, when p=1 if the above description can be proved, it ispossible to prove that at least one CL6 is present also when p=2, 3 ifC#1.1 and C#1.2 hold true in the same way of thinking. Therefore, whenp=1, q=0, if (a_(#0,1,i) mod 3, a_(#0,1,j) mod 3, a#_(0,1,k) mod 3)=(0,0, 0)∪(1, 1, 1)∪(2, 2, 2) holds true, it is possible to prove that atleast one CL6 is present.

In X₁(D) when q=0 is assumed for a parity check polynomial thatsatisfies 0 of the TV3-LDPC-CC in equation 48, if two or fewer terms arepresent, C#1.1 is never satisfied.

In X₁(D) when q=0 is assumed for a parity check polynomial thatsatisfies 0 of the TV3-LDPC-CC in equation 48, if three terms arepresent and (a_(#q,p,i) mod 3,a_(#q,p,j) mod 3, a_(#q,p,k) mod 3)=(0, 0,0)∪(1, 1, 1)∪(2, 2, 2) is satisfied, the parity check polynomial thatsatisfies 0 of q=0 can be represented by equation 49.

$\begin{matrix}{\mspace{20mu}\lbrack 49\rbrack} & \; \\{{{\left( {D^{a_{{\# 0}{.1}{.1}}} + D^{a_{{\# 0}{.1}{.2}}} + \; D^{a_{{\# 0}{.1}{.3}}}} \right){X_{1}(D)}} + {\left( {D^{a_{{\# 0}{.2}{.1}}} + D^{a_{{\# 0}{.2}{.2}}} + \ldots + D^{a_{{\# 0}{{.2}.r}\; 2}}} \right){X_{2}(D)}} + \ldots + {\left( {D^{a_{{{\# 0}.n} - 1.1}} + D^{a_{{{\# 0}.n} - 1.2}} + \ldots + D^{a_{{{\# 0}.n} - {1.r\; n} - 1}}} \right){X_{n - 1}(D)}} + {\left( {D^{b_{{\# 0}{.1}}} + D^{b_{{\# 0}{.2}}} + \ldots + D^{b_{{\# 0}.s}}} \right){P(D)}}} = {{{\left( {D^{a_{{\# 0}{.1}{.3}^{{{+ 3}\;\gamma} + {3\;\delta}}}} + D^{a_{{\# 0}{.1}{.3}^{{+ 3}\;\delta}}} + D^{a_{{\# 0}{.1}{.3}}}} \right){X_{1}(D)}} + {\left( {D^{a_{{\# 0}{.2}{.1}}} + D^{a_{{\# 0}{.2}{.2}}} + \ldots + D^{a_{{\# 0}{{.2}.r}\; 2}}} \right){X_{2}(D)}} + \ldots + {\left( {D^{a_{{{\# 0}.n} - 1.1}} + D^{a_{{{\# 0}.n} - 1.2}} + \ldots + D^{a_{{{\# 0}.n} - {1.r\; n} - 1}}} \right){X_{n - 1}(D)}} + {\left( {D^{b_{{\# 0}{.1}}} + D^{b_{{\# 0}{.2}}} + \ldots + D^{b_{{\# 0}.s}}} \right){P(D)}}} = 0}} & \left( {{Equation}\mspace{14mu} 49} \right)\end{matrix}$

Here, even when a_(#0,1,1)> a_(#0,1,2)> a_(#0,1,3) is assumed,generality is not lost, and γ and δ become natural numbers. In thiscase, when the term relating to X₁(D) when q=0 in equation 49, that is,(D^(a#0,1,3+3)Γ^(+δ)+D^(a#0,1,3+3δ)+D^(a#0,1,3)) X₁(D) is focused upon,a sub-matrix generated by extracting only a part relating to X₁(D) inparity check matrix H is represented as shown in FIG. 35.

In FIG. 35. h_(1,X1) and h_(2,X1) are vectors generated by extractingonly portions relating to X₁(D) of the parity check polynomial thatsatisfies 0 of equation 48 when q=1,2 respectively. In this case, therelationship as shown in FIG. 35 holds true because <1> of feature 1holds true. Therefore, as shown in FIG. 35, CL6 formed of “1” indicatedby Δ necessarily occurs only in a sub-matrix generated by extractingonly the portion relating to X₁(D) of the parity check matrix inequation 49 regardless of the values of γ and δ.

When four or more X₁(D)-related terms are present, three terms areselected from among four or more terms and when (a_(#0,1,i) mod3,a_(#0,1,j) mod 3, a_(#0,1,k) mod 3)=(0, 0, 0)∪(1, 1, 1)∪(2, 2, 2)holds true for the selected three terms, loop 6 is formed as shown inFIG. 35.

As described above, when q=0, if (a_(#0,1,1) mod 3,a_(#0,1,j) mod3,a_(#0,1,k) mod 3)=(0, 0, 0)∪(1, 1, 1)∪(2, 2, 2) holds true for X₁(D),loop 6 is present. Furthermore, also for X₂(D), . . . , X_(n−1)(D),P(D),by substituting X₁(D) for this, at least one CL6 occurs when C#1.1 orC#1.2 holds true.

Furthermore, in the same way of thinking, also for when q=2, 3, at leastone CL6 is present when C#1.1 or C#1.2 is satisfied. Therefore, in theparity check polynomial that satisfies 0 of equation 48, when C#1.1 orC#1.2 holds true, at least one loop 6 is generated.

(End of Proof)

Example

Consider a case where (D⁹+D³+1)X₁(D) is present in the parity checkpolynomial that satisfies 0 of equation 48 when q=0. The vectorgenerated by extracting the X₁(D)-related portion in parity check matrixH is represented as shown in FIG. 36 and CL6 is present. However,[1000001001] in FIG. 36 is a vector generated by extracting only theX₁(D)-related portion in the parity check polynomial that satisfies 0 ofequation 48 when q=0.

The parity check polynomial that satisfies #q-th 0 of the TV3-LDPC-CC ofa coding rate of (n−1)/n which will be described hereinafter is providedbelow based on equation 42 (q=0, 1, 2).

$\begin{matrix}{\mspace{79mu}\lbrack 50\rbrack} & \; \\{{{\left( {D^{a_{{\# q},1,1}} + D^{a_{{\# q},1,2}} + D^{a_{{\# q},1,3}}} \right){X_{1}(D)}} + {\left( {D^{a_{{\# q},2,1}} + D^{a_{{\# q},2,2}} + D^{a_{{\# q},2,3}}} \right){X_{2}(D)}} + \ldots + {\left( {D^{a_{{{\# q} - n},1,1}} + D^{a_{{{\# q} - n},1,2}} + D^{a_{{{\# q} - n},1,3}}} \right){X_{n - 1}(D)}} + {\left( {D^{b_{{\# q},1}} + D^{b_{{\# q},2}} + D^{b_{{\# q},3}}} \right){P(D)}}} = {{{\left( {D^{a_{{\# q},1,1}} + D^{a_{{\# q},1,2}} + 1} \right){X_{1}(D)}} + {\left( {D^{a_{{\# q},2,1}} + D^{a_{{\# q},2,2}} + 1} \right){X_{2}(D)}} + \ldots + {\left( {D^{a_{{\# q},{n - 1},1}} + D^{a_{{\# q},{n - 1},2}} + 1} \right){X_{n - 1}(D)}} + {\left( {D^{b_{{\# q},1}} + D^{b_{{\# q},2}} + 1} \right){P(D)}}} = 0}} & \left( {{Equation}\mspace{14mu} 50} \right)\end{matrix}$

Here, in equation 50, it is assumed that there are three terms in X₁(D),X₂(D), . . . , X_(n−1)(D), and P(D) respectively.

Since a_(#q,p,3) mod 3=0,b_(#q,3) mod 3=0 in equation 50, (a_(#q,p,1)mod 3, a_(#q,p,2) mod 3)=(0, 0), (b_(#q,1) mod 3, b_(#q,2) mod 3)=(0, 0)should not be satisfied to suppress the occurrence of CL6 in accordancewith theorem 1. Therefore, Table 1 can be created as a condition of(a_(#q,p,1) mod 3, a_(#q,p,2) mod 3), (b_(#q,1) mod 3, b_(#q,2) mod 3)so that the LDPC code becomes a regular LDPC code except the conditionof (a_(#q.p,1) mod 3, a_(#q,p,2) mod 3)=(0, 0), (b_(#q,1) mod 3,b_(#q,2)mod 3)=(0, 0) and in accordance with feature 1.

TABLE 1 (a_(#0,p,1) mod 3, a_(#0,p,2) (a_(#1,p,1) mod 3, a_(#1,p,2)(a_(#2,p,1) mod 3, a_(#2,p,2) mod 3) mod 3) mod 3) (b_(#0,1) mod 3,b_(#0,2) mod (b_(#1,1) mod 3, b_(#1,2) (b_(#2,1) mod 3, b_(#2,2) 3) mod3) mod 3) values values values C#1 [0, 1] [0, 1] [0, 1] C#2 [0, 1] [0,2] [1, 2] C#3 [0, 1] [1, 2] [1, 1] C#4 [0, 2] [0, 2] [0, 2] C#5 [0, 2][1, 2] [0, 1] C#6 [0, 2] [2, 2] [1, 2] C#7 [1, 1] [0, 1] [1, 2] C#8 [1,1] [1, 1] [1, 1] C#9 [1, 2] [0, 1] [0, 2] C#10 [1, 2] [0, 2] [2, 2] C#11[1, 2] [1, 1] [0, 1] C#12 [1, 2] [1, 2] [1, 2] C#13 [2, 2] [1, 2] [0, 2]C#14 [2, 2] [2, 2] [2, 2]

In Table 1, when (a_(#q,p,1) mod 3, a_(#q,p,2) mod 3) and (b_(#q,1) mod3, b_(#q,2) mod 3) satisfy any of C#1 to C#14, a regular LDPC code canbe created. For example, the X_(p)(D)-related term in equation 50 is(D^(a#0,p,1)+D^(a#0,p,2)+1)X_(q)(D) when q=0(D^(a#1,p,1)+D^(a#1,p,2)+1)Xq(D) when q=1 and(D^(a#2,p,1)+D^(a#2,p,2)+1)X_(q)(D) when q=2, and in this case,(a_(#0,p,1) mod 3, a_(#0,p,2) mod 3),(a_(#1,p,1) mod 3, a_(#1,p,2) mod3),(a_(#2,p,i) mod 3, a_(#2,p,2) mod 3) satisfies any of C#1 to C#14.

However, (A,B)≡[a,b] becomes (A,B)=(a,b)∪(b,a). Similarly, theP(D)-related term in equation 50 is (D^(b#0,1)+D^(b#0,2)+1)P(D) whenq=0, (D^(b#1,1)+D^(b#1,2)+1)P(D) when q=1 and(D^(b#2,1)+D^(b#2,2)+1)P(D) when q=2. and in this case, (b_(#0,1) mod 3,b_(#0,2) mod 3), (b_(#1,1) mod 3, b_(#1,2) mod 3),(b_(#2,1) mod 3,b_(#2,2) mod 3) satisfies any of C#1 to C#14.

Example of Code Search:

Table 2 shows an example of TV3-LDPC-CCs of coding rates of R=1/2 and5/6 searched by generating parity check polynomials that satisfy 0 ofequation 46 by generating random numbers without constraints.

TABLE 2 Code Index K_(max) R Coefficient of equation 46 #1 600 1/2(A_(X1,0)(D), B₀(D)) = (D⁵⁴⁹ + D⁵⁰⁹ + 1, D²⁴⁸ + D³³ + 1) (A_(X1,1)(D),B₁(D)) = (D³⁹⁸ + D²¹⁵ + 1, D⁴⁵⁸ + D³⁷⁶ + 1) (A_(X1,2)(D), B₂(D)) =(D⁴¹² + D²⁸⁷ + 1, D³⁸⁸ + D³³¹ + 1) #2 600 5/6 (A_(X1,0)(D), A_(X2,0)(D),A_(X3,0)(D), A_(X4,0)(D), A_(X5,0)(D), B₀(D)) = (D⁴⁴⁸ + D¹³¹ + 1, D⁴¹⁶ +D²⁴² + 1, D¹¹⁰ + D³⁹ + 1, D³⁵¹ + D²³⁵ + 1, D²⁹² + D¹⁵⁵ + 1, D⁵⁸⁷ +D⁴⁹⁶ + 1) (A_(X1,1)(D), A_(X2,1)(D), A_(X3,1)(D), A_(X4,1)(D),A_(X5,1)(D), B₁(D)) = (D²²⁶ + D¹⁶ + 1, D⁴⁷³ + D²⁶⁴ + 1, D⁴¹³ + D²⁶⁰ + 1,D⁴⁴² + D¹⁰² + 1, D⁵³⁵ + D¹⁵⁰ + 1, D⁴⁹ + D⁶ + 1) (A_(X1,2)(D),A_(X2,2)(D), A_(X3,2)(D), A_(X4,2)(D), A_(X5,2)(D), B₂(D)) = (D⁵⁶⁴ +D¹²⁹ + 1, D⁴¹⁶ + D¹⁴¹ + 1, D⁵²² + D⁴⁸⁵ + 1, D¹⁶⁶ + D⁵⁶ + 1, D³⁵³ +D¹²³ + 1, D³⁷² + D¹³⁴ + 1)

Table 3 shows an example of TV3-LDPC-CCs of coding rates of R=1/2 and5/6 searched by generating parity check polynomials that satisfy 0 ofequation 46 by generating random numbers by providing constraints. To bemore specific, code indices #3 and #5 in Table 3 show an example ofTV3-LDPC-CCs of coding rates of R=1/2 and 5/6 searched in X₁(D), . . . ,X_(n−1)(D), and P(D) of equation 46 when constraints are provided so asto satisfy any of C#1 to C#12 in Table 1. Furthermore, code indices #4and #6 in Table 3 show an example of TV3-LDPC-CCs of coding rates ofR=1/2 and 5/6 searched in X₁(D), . . . , X_(n−1)(D), and P(D) ofequation 46 when constraints are provided so as to satisfy any of C#1 toC#12 in Table 1.

TABLE 3 Code Index K_(max) R Coefficient of equation 46 #1 600 1/2(A_(X1,0)(D), B₀(D)) = (D⁵⁴⁵ + D⁴⁴⁸ + 1, D⁵⁰⁹ + D⁵⁰⁶ + 1) (A_(X1,1)(D),B₁(D)) = (D⁵¹⁸ + D⁴⁵⁴ + 1, D⁵⁷⁸ + D⁷⁴ + 1) (A_(X1,2)(D), B₂(D)) =(D⁴⁵⁸ + D³⁸⁵ + 1, D³¹⁷ + D⁸⁶ + 1) #4 600 1/2 (A_(X1,0)(D), B₀(D)) =(D⁴⁵¹ + D²⁷³ + 1, D⁵²⁰ + D³⁴⁷ + 1) (A_(X1,1)(D), B₁(D)) = (D⁵⁸¹ + D³³⁷ +1, D⁴⁵² + D²⁸ + 1) (A_(X1,2)(D), B₂(D)) = (D⁴⁸⁴ + D²³⁹ + 1, D⁵⁸⁰ +D⁵³³ + 1) #5 600 5/6 (A_(X1,0)(D), A_(X2,0)(D), A_(X3,0)(D),A_(X4,0)(D), A_(X5,0)(D), B₀(D)) = (D⁴⁵² + D⁴⁵⁰ + 1, D⁴⁷³ + D⁴³⁵ + 1,D³³² + D¹⁵² + 1, D⁵⁶⁸ + D¹⁷⁴ + 1, D⁴⁹⁶ + D²⁴⁸ + 1, D¹⁵⁶ + D¹⁰⁶ + 1)(A_(X1,1)(D), A_(X2,1)(D), A_(X3,1)(D), A_(X4,1)(D), A_(X5,1)(D), B₁(D))= (D⁵⁶⁰ + D¹⁴ + 1, D⁴⁶⁰ + D³⁵⁶ + 1, D⁴⁷² + D³⁷⁴ + 1, D⁴³⁴ + D³⁰⁴ + 1,D³⁵¹ + D¹⁷⁹ + 1, D³⁹⁷ + D²⁷³ + 1) (A_(X1,2)(D), A_(X2,2)(D),A_(X3,2)(D), A_(X4,2)(D), A_(X5,2)(D), B₂(D)) = (D⁴⁴⁰ + D²¹⁴ + 1, D²⁵⁶ +D¹¹⁴ + 1, D⁵⁸² + D²⁶ + 1, D⁵⁸⁰ + D²¹¹ + 1, D³⁷⁷ + D¹⁴⁹ + 1, D¹³⁹+D⁸¹ + 1) #6 600 5/6 (A_(X1,0)(D), A_(X2,0)(D), A_(X3,0)(D), A_(X4,0)(D),A_(X5,0)(D), B₀(D)) = (D⁵⁸³ + D²¹⁸ + 1, D⁴³¹ + D²⁵⁶ + 1, D⁵⁸⁷ + D¹³ + 1,D²⁴⁴ + D⁶² + 1, D⁵⁶⁸ + D³⁴⁷ + 1, D²⁸⁴ + D¹⁰³ + 1) (A_(X1,1)(D),A_(X2,1)(D), A_(X3,1)(D), A_(X4,1)(D), A_(X5,1)(D), B₁(D)) = (D⁴⁸¹ +D⁸³ + 1, D³⁴⁷ + D⁴¹³ + 1, D⁴⁵² + D¹⁹⁰ + 1, D⁵⁹³ + D⁵⁶⁵ + 1, D⁴⁷³ +D²⁸³ + 1, D⁵⁶⁸ + D¹⁴³ + 1)

Table 4 shows the result of evaluating the numbers of CL4's and CL6'sfor each parity check polynomial that satisfies 0 of the TV3-LDPC-CC inTable 2 and Table 3. Since none of TV3-LDPC-CCs of code index #1 to codeindex #6 satisfies theorem 1, the number of CL6's is small and there isno significant difference in the number of CL6's when compared at thesame coding rate. Furthermore, there is no CL4 in TV3-LDPC-CCs of codeindex #1 to code index #6.

TABLE 4 Code Number of Number of Index CL I_(c) = 4 CL I_(c) = 6 #1 [0,0, 0] [0, 0, 0] #2 [0, 0, 0] [4, 4, 6] #3 [0, 0, 0] [0, 0, 0] #4 [0, 0,0] [0, 0, 0] #5 [0, 0, 0] [4, 4, 6] #6 [0, 0, 0] [3, 3, 1]

It is clear from Table 4 that the condition in Table 1 is important inreducing the number of short cycles and creating a regular LDPC code. Inaddition to Table 2 and Table 3, TV3-LDPC-CCs were created and errorcorrection capability was evaluated. In the light of the results,conditions under which high error correction capability is obtained andconditions under which high error correction capability is not obtainedwill be described below.

Condition under which high error correction capability is not obtained:

<1> When the parity check polynomial that satisfies #q-th 0 of aTV3-LDPC-CC of a coding rate of (n−1)/n can be represented as shown inequation 50 (q=0, 1, 2), a singular (irregular) LDPC code is formed.

Condition under which high error correction capability is obtained:

<2> When the parity check polynomial that satisfies #q-th 0 of aTV3-LDPC-CC of a coding rate of (n−1)/n can be represented as shown inequation 50 (q=0, 1, 2), X₁(D), . . . , X_(n−1)(D), and P(D) in equation50 satisfies C#12 in Table 1.

<3> When the parity check polynomial that satisfies #q-th 0 of aTV3-LDPC-CC of a coding rate of (n−1)/n can be represented as shown inequation 50 (q=0, 1, 2), if X_(a)(D) in X₁(D), . . . , X_(n−1)(D), andP(D) of equation 50 satisfies C#i in Table 1, some of X₁(D), . . . ,X_(n−1)(D), and P(D) satisfy C#j(j≠i) in Table 1.

TV3-LDPC-CCs of code index #3 and code index #5 in Table 3 satisfy theabove condition in <3>.

A case has been described in the present embodiment where the number ofterms X₁(D), X₂(D), . . . , X_(n−1)(D), and P(D) in a TV3-LDPC-CCdefined by the parity check polynomial of equation 50, that is, eachparity check polynomial that satisfies 0 is three. The number of termsis not limited to this, and high error correction capability may belikely to be obtained even when the number of terms of any of X₁(D),X₂(D), . . . , X_(n−1)(D), and P(D) of equation 50 is 1 or 2. Forexample, the following method is available as a method of setting thenumber of terms of X₁(D) to 1 or 2. When the time varying period is 3, aparity check polynomial satisfying three 0's is present, and the numberof terms of X₁(D) is assumed to be 1 or 2 for all parity checkpolynomials that satisfy three 0's. Alternatively, instead of settingthe number of terms of X₁(D) to 1 or 2 in all parity check polynomialsthat satisfy three 0's, the number of terms of X₁(D) may be set to 1 or2 in parity check polynomials that satisfy any (two or fewer) 0's of theparity check polynomials that satisfy three 0's. The same applies toX₂(D), . . . , X_(n−1)(D) as well. However, the condition in Table 1 isnot satisfied for the deleted terms (deleted terms of any of X₁(D),X₂(D), . . . , X_(n−1)(D), and P(D)).

Furthermore, high error correction capability may be obtained also whenthe number of terms of any of X₁(D), X₂(D), . . . , X_(n−1)(D), and P(D)is 4 or more. For example, the following method is available as a methodof setting the number of terms of X₁(D) to 4 or greater. When the timevarying period is 3, there is a parity check polynomial satisfying three0's, but the number of terms of X₁(D) is set to 4 or greater for allparity check polynomials satisfying three 0's. Alternatively, instead ofsetting the number of terms of X₁(D) to 4 or greater in all parity checkpolynomials that satisfy three 0's, the number of terms of X₁(D) may beset to 4 or greater in parity check polynomials satisfying any (two orfewer) 0's among the parity check polynomials satisfying three 0's. Thesame applies to X₂(D), . . . , X_(n−1)(D) as well. In this case, thecondition of Table 1 is satisfied for none of increased terms (increasedterms of any of X₁(D), X₂(D), . . . , X_(n−1)(D), and P(D)).

Embodiment 7

The present embodiment will be describe a time-varying LDPC-CC of acoding rate of R=(n−1)/n based on a parity check polynomial again. Bitsof information bits of X₁, X₂, . . . , X_(n−1), and parity bit P atpoint in time j are represented by X_(1,j),X_(2,j), . . . , X_(n−1,j)and P_(j) respectively. Vector u_(j) at point in time j is representedby u_(j)=(X_(1,j), X_(2,j), . . . , X_(n−1,j), P_(j)). Furthermore, theencoded sequence is represented by u=(u₀, u₁, . . . , u_(j), . . .)^(T). When D is assumed to be a delay operator, the polynomials ofinformation bits X₁, X₂, . . . , X_(n−1) are represented by X₁(D),X₂(D), . . . , X_(n−1)(D) and the polynomial of parity bit P isrepresented by P(D). In this case, consider a parity check polynomialsatisfying 0 represented by equation 51.

$\begin{matrix}{\mspace{79mu}\lbrack 51\rbrack} & \; \\{{\left( {D^{a_{1.1}} + D^{a_{1.2}} + \ldots + D^{a_{1.r\; 1}} + 1} \right){X_{1}(D)}} + {\left( {D^{a_{2.1}} + D^{a_{2.2}} + \ldots + D^{a_{2.r\; 2}} + 1} \right){X_{2}(D)}} + \ldots + {\left( {D^{a_{n - 1.1}} + D^{a_{n - 1.2}} + \ldots + D^{a_{n - {1.r\; n} - 1}} + 1} \right){X_{n - 1}(D)}} + {\left( {D^{b_{1}} + D^{b_{2}} + \ldots + D^{b_{c}} + 1} \right){P(D)}} + 0} & \left( {{Equation}\mspace{14mu} 51} \right)\end{matrix}$

In equation 51, assume that a_(p,q) (p=1, 2, . . . , n−1; q=1, 2, . . ., r_(p)) and b_(s) (s=1, 2, . . . , ε) are natural numbers).Furthermore, a_(p,y)≠a_(p,z) is satisfied for y,z=1, 2, . . . , r_(p),y≠z of ^(∀)(y,z). Furthermore, b_(y)≠b_(z) is satisfied for y,z=1, 2, .. . , ε, ^(∀)(y,z) of y≠z. Here, ∀ is a universal quantifier.

To create an LDPC-CC of a coding rate of R=(n−1)/n and a time varyingperiod of m, a parity check polynomial based on equation 51 is prepared.In this case, an i-th (i=0, 1, . . . , m−1) parity check polynomial isrepresented by equation 52.[52]A _(X1,i)(D)X ₁(D)+A _(X2,i)(D)X ₂(D)+ . . . +A _(Xn−1,i)(D)X_(n−1)(D)+B _(i)(D)P(D)=0  (Equation 52)

In equation 52, maximum degrees of D of A_(Xδ,i)(D) (δ=1, 2, . . . ,n−1) and B_(i)(D) are represented by Γ_(Xδ,i) and Γ_(P,i) respectively.Assume that a maximum value of Γ_(Xδ,i) and Γ_(P,i) is Γ_(i). Assumethat a maximum value of Γ_(i) (i=1, 1, . . . , m−1) is Γ. When encodedsequence u is taken into account, vector h_(i) corresponding to the i-thparity check polynomial is represented by equation 53 using Γ.[53]h _(i)=[h _(i,Γ) ,h _(i,Γ−1) , . . . ,h _(i,1) ,h _(i,0)]  (Equation 53)

In equation 53, h_(i,v) (v=0, 1, . . . , Γ) is a vector of 1×n and isrepresented by equation 54.[54]h _(i,v)=[α_(i,v,X1),α_(i,v,X2), . . . ,α_(i,v,Xn−1),β_(i,x)]  (Equation54)

This is because the parity check polynomial of equation 52 hasα_(i,v,Xw)D^(v)X_(w)(D) and β_(i,v)D^(v)P(D) (where w=1, 2, . . . , n−1,and, α_(i,v,Xw,)β_(i,v)∈[0, 1]). In this case, the parity checkpolynomial satisfying 0 of equation 52 has D⁰X₁(D), D⁰X₂(D), . . . ,D⁰X_(n−1)(D) and D⁰P(D), and thereby satisfies equation 55.

$\begin{matrix}\lbrack 55\rbrack & \; \\{h_{i,0} = \left\lbrack \underset{\underset{n}{︸}}{1\mspace{14mu}\ldots\mspace{14mu} 1} \right\rbrack} & \left( {{Equation}\mspace{14mu} 55} \right)\end{matrix}$

In equation 55), Λ(k)=Λ(k+m) is satisfied for ^(∀)k, where Λ(k)corresponds to h_(i) of a k-th row of the parity check matrix.

Using equation 53, equation 54 and equation 55, the parity check matrixof an LDPC-CC based on the parity check polynomial of a coding rate ofR=(n−1)/n and a time varying period of m is represented by equation 56.

$\begin{matrix}\lbrack 56\rbrack & \; \\{H = \begin{bmatrix}\ddots & \; & \; & \; & \; & \; & \; & \ddots & \; & \; & \; & \; & \; & \; & \; & \; \\\; & h_{0,\Gamma} & h_{0,{\Gamma - 1}} & \ldots & \ldots & \ldots & \ldots & \ldots & h_{0,0} & \; & \; & \; & \; & \; & \; & \; \\\; & \; & h_{1,\Gamma} & \ldots & \ldots & \ldots & \ldots & \ldots & h_{1,1} & h_{1,0} & \; & \; & \; & \; & \; & \; \\\; & \; & \; & \ddots & \; & \; & \; & \; & \; & \; & \ddots & \; & \; & \; & \; & \; \\\; & \; & \; & \; & h_{{m - 1},\Gamma} & h_{{m - 1},{\Gamma - 1}} & \ldots & \ldots & \ldots & \ldots & \ldots & h_{{m - 1},0} & \; & \; & \; & \; \\\; & \; & \; & \; & \; & h_{0,\Gamma} & \ldots & \ldots & \ldots & \ldots & \ldots & h_{0,1} & h_{0,0} & \; & \; & \; \\\; & \; & \; & \; & \; & \; & \ddots & \; & \; & \; & \; & \; & \; & \ddots & \; & \; \\\; & \; & \; & \; & \; & \; & \; & h_{{m - 1},\Gamma} & \ldots & \ldots & \ldots & \ldots & \ldots & \ldots & h_{{m - 1},0} & \; \\\; & \; & \; & \; & \; & \; & \; & \; & \ddots & \; & \; & \; & \; & \; & \; & \ddots\end{bmatrix}} & \left( {{Equation}\mspace{14mu} 56} \right)\end{matrix}$

The disclosure of Japanese Patent Application No. 2008-334028, filed onDec. 26, 2008, including the specification, drawings and abstract isincorporated herein by reference in its entirety.

INDUSTRIAL APPLICABILITY

The present invention is suitable for use as an encoding method, encoderand decoder or the like for performing erasure correction using lowdensity parity check codes (LDPC codes).

REFERENCE SIGNS LIST

-   100, 200 Communication apparatus-   20 Communication channel-   110 Packet generation and known packet insertion section-   120 Erasure correction encoding-related processing section-   121 Erasure correction encoding section-   122,234 known information packet deleting section-   1211 Rearranging section-   1212 Encoding section (parity packet generation section)-   130 Error correcting encoding section-   131 Known information insertion section-   132 Encoder-   133 Known information deleting section-   140, 250 Transmitting apparatus-   141 Modulation section-   142 Control information generation section-   143 Transmitting section-   150, 210 Receiving apparatus-   220 Error correcting decoding section-   221 Known information log likelihood ratio insertion section-   222 Decoder-   223 known information deleting section-   230 Erasure correction decoding related processing section-   231 Error detection section-   232 Known information packet insertion section-   233 Erasure correction decoding section-   234 Known information packet deleting section-   240 Packet decoding section-   500 LDPC-CC encoding section-   510 Data computing section-   520 Parity computing section-   530 Weight control section-   540 Mod 2 adder

The invention claimed is:
 1. A transmission method comprising: receivinginformation data blocks to be transmitted; adding, by a signalprocessing circuit, at least one known information data block to theinformation data blocks to generate first data blocks; error-correctioncoding, by the signal processing circuit, the first data blocks togenerate first coded data blocks including parity data blocks such thatthe first coded data blocks satisfy a first code rate; removing, by thesignal processing circuit, the at least one known information data blockfrom the first coded data blocks to generate second coded data blocks,the second coded data blocks satisfying a second code rate differentfrom the first code rate; modulating, by the signal processing circuit,the second coded data blocks using a modulation scheme to generate amodulated signal, and; transmitting, from an antenna, the modulatedsignal, wherein a number of data blocks included in the at least oneknown information data block depends on a number of the information datablocks such that the first code rate is fixed regardless of the numberof the information data blocks.
 2. The transmission method according toclaim 1, wherein the at least one known information data block consistsof a plurality of zeroed bits.
 3. A transmission apparatus comprising: adata block adding circuit configured to add at least one knowninformation data block to received information data blocks to generatefirst data blocks; a coding circuit configured to performerror-correction coding on the first data blocks to generate first codeddata blocks including parity data blocks such that the first coded datablocks satisfy a first code rate; a removing circuit configured toremove the at least one known information data block from the firstcoded data blocks to generate second coded data blocks, the second codeddata blocks satisfying a second code rate different from the first coderate; and a modulating circuit configured to modulate the second codeddata blocks using a modulation scheme to generate a modulated signal;and transmitter circuit configured to transmit the modulated signal,wherein a number of data blocks included in the at least one knowninformation data block depends on a number of the received informationdata blocks such that the first code rate is fixed regardless of thenumber of the received information data blocks.
 4. The transmissionapparatus according to claim 3, wherein the at least one knowninformation data block consists of a plurality of zeroed bits.
 5. Areception method comprising: Receiving, by a receiver, a modulatedsignal; demodulating the modulated signal to generate second coded datablocks; and error-correction decoding the second coded data blocks,wherein a transmission apparatus has performed an encoding process onthe modulated signal, the encoding process including: adding at leastone known information data block to received information data blocks togenerate first data blocks; error-correction coding the first datablocks to generate first coded data blocks including parity data blockssuch that the first coded data blocks satisfy a first code rate;removing the at least one known data block from the first coded datablocks to generate the second coded data blocks, the second coded datablocks satisfying a second code rate different from the first code rate;and modulating the second coded data blocks using a modulation scheme togenerate the modulated signal, wherein a number of data blocks includedin the at least one known information data block depends on a number ofthe received information data blocks such that the first code rate isfixed regardless of the number of the information data blocks.
 6. Thereception method according to claim 5, wherein the at least one knowninformation data block consists of a plurality of zeroed bits.
 7. Atransmission method comprising: receiving information data blocks to betransmitted; adding, by a signal processing circuit, at least one knowninformation data block to the information data blocks to generate firstdata blocks; error-correction coding, by the signal processing circuit,the first data blocks to generate first coded data blocks includingparity data blocks such that the first coded data blocks satisfy a firstcode rate; removing, by the signal processing circuit, the at least oneknown information data block from the first coded data blocks togenerate second coded data blocks, the second coded data blockssatisfying a second code rate different from the first code rate;modulating, by the signal processing circuit, the second coded datablocks using a modulation scheme to generate a modulated signal; andtransmitting, from an antenna, the modulated signal, wherein a number ofdata blocks included in the at least one known information data blockdepends on a number of the information data blocks and the first coderate.